CN113392489A - Calculation method of distributed hydrodynamic model of river system - Google Patents
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Abstract
The invention discloses a calculation method of a distributed hydrodynamic model of a river system, which comprises the following steps: acquiring water system distribution information, a water system distribution data set and a water system relation network; acquiring data information of each branch according to the water system distribution information, and further acquiring a hydrodynamic model database; and obtaining a model calculation sequence according to the water system relation network and the hydrodynamic model database, obtaining a calculation equipment matching sequence by combining with the distributed calculation equipment information, calculating according to the calculation equipment matching sequence to obtain a water system calculation result, and finally obtaining flood prevention scheduling information. The technical problem that an accurate forecasting and reasonable flood prevention scheduling scheme cannot be rapidly provided in the prior art is solved, so that the flood prediction with high speed and high precision is realized, and the technical effect of the effective and reasonable flood prevention scheduling scheme is provided. The application also provides a computing system of the distributed hydrodynamic model of the river system, and the computing system also has the beneficial effects.
Description
The technical field is as follows:
the invention relates to the field of artificial intelligence, in particular to a calculation method of a distributed hydrodynamic model of a river system.
Background art:
water is a valuable resource essential for human production and life, but the naturally-existing state of the water does not completely meet the needs of human beings, and the water can be effectively utilized only by reasonably controlling the water in a specific mode. The river channels of China are numerous, the drainage basins are wide, and due to the fact that the regions are wide, the climate and terrain differences are very large, the fact that how to efficiently prevent flood and fight against flood becomes an important problem of social attention. The fundamental purpose of flood control and flood fighting is to protect the life safety of people. Therefore, how to accurately and quickly measure flood discharge, flood control and flood removal capacity of the river water system is very important. Because the river water system in China is complex, the landform and the landform are changeable, and in addition, the water level is greatly influenced by human factors, the difficulty in accurately calculating the river water system is great, and the urgent need to solve the problem of how to accurately and quickly forecast flood disasters is needed.
In the process of implementing the technical scheme of the invention in the embodiment of the present application, the inventor of the present application finds that the above-mentioned technology has at least the following technical problems:
the technical problem that an accurate forecast and reasonable flood prevention scheduling scheme cannot be rapidly provided in the prior art exists, so that decision making and measure taking of relevant departments are not enough in time, and further the economy and even the life safety of people are greatly threatened.
The invention content is as follows:
in view of the above, embodiments of the present application provide a method and a system for calculating a distributed hydrodynamic model of a river water system, where the method includes: acquiring water system distribution information; acquiring a water system distribution data set according to the water system distribution information; acquiring a water system relation network according to the water system distribution data set; obtaining data information of each branch according to the water system distribution information, wherein the data information of each branch comprises water flow, topography, water depth, hydraulic engineering and flood control facilities; constructing a hydrodynamic model based on the data information of each branch to obtain a hydrodynamic model database; obtaining a model calculation sequence according to the water system relation network and the hydrodynamic model database; obtaining distributed computing device information; obtaining a computing device matching sequence according to the model computing sequence and the distributed computing device information, and establishing communication connection between the computer device and the corresponding hydrodynamic model; calculating according to the matching sequence of the calculating equipment to obtain a water system calculating result; and obtaining flood prevention scheduling information according to the water system calculation result. The flood prevention scheduling method solves the technical problem that an accurate forecasting and reasonable flood prevention scheduling scheme cannot be rapidly provided in the prior art, achieves flood prediction with high speed and high precision, provides the technical effect of an effective and reasonable flood prevention scheduling scheme, and provides enough time for relevant departments to carry out flood prevention scheduling work arrangement.
In view of the above problems, the embodiments of the present application provide a computing system of a distributed hydrodynamic model of a river water system.
In a first aspect, the present application provides a method for calculating a distributed hydrodynamic model of a river water system, where the method is implemented by a system for calculating a distributed hydrodynamic model of a river water system, where the method includes: acquiring water system distribution information; acquiring a water system distribution data set according to the water system distribution information; acquiring a water system relation network according to the water system distribution data set; obtaining data information of each branch according to the water system distribution information, wherein the data information of each branch comprises water flow, topography, water depth, hydraulic engineering and flood control facilities; constructing a hydrodynamic model based on the data information of each branch to obtain a hydrodynamic model database; obtaining a model calculation sequence according to the water system relation network and the hydrodynamic model database; obtaining distributed computing device information; obtaining a computing device matching sequence according to the model computing sequence and the distributed computing device information, and establishing communication connection between the computer device and the corresponding hydrodynamic model; calculating according to the matching sequence of the calculating equipment to obtain a water system calculating result; and obtaining flood prevention scheduling information according to the water system calculation result.
In another aspect, the present application further provides a computation system of a distributed hydrodynamic model of a river water system, for performing the computation method of the distributed hydrodynamic model of the river water system according to the first aspect, wherein the system includes: a first obtaining unit: the first obtaining unit is used for obtaining water system distribution information; a second obtaining unit: the second obtaining unit is used for obtaining a water system distribution data set according to the water system distribution information; a third obtaining unit: the third obtaining unit is used for obtaining a water system relation network according to the water system distribution data set; a fourth obtaining unit: the fourth obtaining unit is used for obtaining data information of each branch according to the water system distribution information, wherein the data information of each branch comprises water flow, topography, water depth, hydraulic engineering and flood control facilities; a fifth obtaining unit: the fifth obtaining unit is used for constructing a hydrodynamic model based on the data information of each tributary to obtain a hydrodynamic model database; a sixth obtaining unit: the sixth obtaining unit is configured to obtain a model calculation sequence according to the water system relationship network and the hydrodynamic model database; a seventh obtaining unit: the seventh obtaining unit is configured to obtain distributed computing device information; an eighth obtaining unit: the eighth obtaining unit is configured to obtain a computing device matching sequence according to the model computing sequence and the distributed computing device information, and the computer device establishes a communication connection with a corresponding hydrodynamic model; a ninth obtaining unit: the ninth obtaining unit is used for calculating according to the calculating equipment matching sequence to obtain a water system calculating result; a tenth obtaining unit: and the tenth obtaining unit is used for obtaining flood prevention scheduling information according to the water system calculation result.
In a third aspect, embodiments of the present application further provide a computing system of a distributed hydrodynamic model of a river water system, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method according to the first aspect when executing the program.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
1. obtaining water system distribution information; acquiring a water system distribution data set according to the water system distribution information; acquiring a water system relation network according to the water system distribution data set; obtaining data information of each branch according to the water system distribution information, wherein the data information of each branch comprises water flow, topography, water depth, hydraulic engineering and flood control facilities; constructing a hydrodynamic model based on the data information of each branch to obtain a hydrodynamic model database; obtaining a model calculation sequence according to the water system relation network and the hydrodynamic model database; obtaining distributed computing device information; obtaining a computing device matching sequence according to the model computing sequence and the distributed computing device information, and establishing communication connection between the computer device and the corresponding hydrodynamic model; calculating according to the matching sequence of the calculating equipment to obtain a water system calculating result; and obtaining flood prevention scheduling information according to the water system calculation result. The flood prevention dispatching method has the advantages that flood prediction with high speed and high precision is achieved, the technical effect of an effective and reasonable flood prevention dispatching scheme is provided, and the flood prevention dispatching work arrangement is given enough time for relevant departments.
2. Through the water conservancy prediction model established on the basis of the neural network model, continuous self-training learning can be carried out according to training data, and through carrying out data training on the water conservancy prediction model, the water conservancy prediction model is more accurate in processing input data, so that the output result of the water conservancy prediction model is more accurate, the accurate data information acquisition is achieved, and the intelligent technical effect of the evaluation result is improved.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Description of the drawings:
in order to more clearly illustrate the embodiments or technical solutions in the prior art of the present invention, the drawings used in the description of the embodiments or prior art will be briefly described below, it is obvious that the drawings in the following description are only exemplary, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a schematic flowchart of a method for calculating a distributed hydrodynamic model of a river system according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of a computing system of a distributed hydrodynamic model of a river water system according to an embodiment of the present disclosure;
FIG. 3 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application;
description of reference numerals:
a first obtaining unit 11, a second obtaining unit 12, a third obtaining unit 13, a fourth obtaining unit 14, a fifth obtaining unit 15, a sixth obtaining unit 16, a seventh obtaining unit 17, an eighth obtaining unit 18, a ninth obtaining unit 19, a tenth obtaining unit 20, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, and a bus interface 305.
The specific implementation mode is as follows:
the embodiment of the application provides a calculation method and a system of a distributed hydrodynamic model of a river system, and solves the technical problems that in the prior art, an accurate forecast and reasonable flood prevention scheduling scheme cannot be quickly provided, so that relevant departments do not have enough time to make decisions and take measures, and further the economic and even life safety of people is greatly threatened. The computer technology is developed rapidly, the specific conditions of a river system are considered comprehensively by utilizing a distributed hydrodynamic model, the calculation method is improved, high-precision measurement and calculation values are given intelligently, a reasonable flood prevention scheduling scheme is given, flood prediction with high speed and high precision is achieved, the technical effect of the effective and reasonable flood prevention scheduling scheme is provided, and the arrangement of flood prevention scheduling work in enough time of relevant departments is provided.
In the following, the technical solutions in the embodiments of the present application will be clearly and completely described with reference to the accompanying drawings, and it is to be understood that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments of the present application, and it should be understood that the present application is not limited by the example embodiments described herein. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application. It should be further noted that, for the convenience of description, only some but not all of the elements relevant to the present application are shown in the drawings.
Summary of the application
Water is a valuable resource essential for human production and life, but the naturally-existing state of the water does not completely meet the needs of human beings, and the water can be effectively utilized only by reasonably controlling the water in a specific mode. The river channels of China are numerous, the drainage basins are wide, and due to the fact that the regions are wide, the climate and terrain differences are very large, the fact that how to efficiently prevent flood and fight against flood becomes an important problem of social attention. The fundamental purpose of flood control and flood fighting is to protect the life safety of people. Therefore, how to accurately and quickly measure flood discharge, flood control and flood removal capacity of the river water system is very important. Because the river water system in China is complex, the landform and the landform are changeable, and in addition, the water level is greatly influenced by human factors, the difficulty in accurately calculating the river water system is great, and the urgent need to solve the problem of how to accurately and quickly forecast flood disasters is needed.
The technical problem that an accurate forecast and reasonable flood prevention scheduling scheme cannot be rapidly provided in the prior art exists, so that decision making and measure taking of relevant departments are not enough in time, and further the economy and even the life safety of people are greatly threatened.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the application provides a calculation method of a distributed hydrodynamic model of a river water system, which is applied to a calculation system of the distributed hydrodynamic model of the river water system, wherein the method comprises the following steps: acquiring water system distribution information; acquiring a water system distribution data set according to the water system distribution information; acquiring a water system relation network according to the water system distribution data set; obtaining data information of each branch according to the water system distribution information, wherein the data information of each branch comprises water flow, topography, water depth, hydraulic engineering and flood control facilities; constructing a hydrodynamic model based on the data information of each branch to obtain a hydrodynamic model database; obtaining a model calculation sequence according to the water system relation network and the hydrodynamic model database; obtaining distributed computing device information; obtaining a computing device matching sequence according to the model computing sequence and the distributed computing device information, and establishing communication connection between the computer device and the corresponding hydrodynamic model; calculating according to the matching sequence of the calculating equipment to obtain a water system calculating result; and obtaining flood prevention scheduling information according to the water system calculation result.
Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.
Example one
Referring to fig. 1, an embodiment of the present application provides a method for calculating a distributed hydrodynamic model of a river system, where the method is applied to a system for calculating a distributed hydrodynamic model of a river system, and the method specifically includes the following steps:
step S100: acquiring water system distribution information;
step S200: acquiring a water system distribution data set according to the water system distribution information;
step S300: acquiring a water system relation network according to the water system distribution data set;
specifically, the river channel refers to a route along which river water flows, and generally refers to a waterway capable of navigation. The water system refers to a water network system consisting of various water bodies such as rivers, lakes and the like in a watershed. The river system is a water network system formed by river water flowing through various routes. Firstly, through various modes such as statistics or data reference, all river water system information in a target area is obtained, including information such as the flow, the flow direction, the basin area, the number of branches, water system attribution and the like of the river water system, and then the water system distribution information can be obtained. Based on the water system distribution information, a water system distribution data set can be obtained by arrangement. The water system distribution data set comprises all basic information of all river systems in the target area, and further, a water system relation network can be obtained by arranging according to the basic information of the river systems, wherein the water system relation network comprises information such as the flow, the flow direction, the area of the flow area, the number and the form of branches, the density of the flow network, the affiliation of the water systems and the like of all the river systems in the target area, and provides a data basis for the calculation of the river systems.
Step S400: obtaining data information of each branch according to the water system distribution information, wherein the data information of each branch comprises water flow, topography, water depth, hydraulic engineering and flood control facilities;
specifically, data information of each branch of the river water system in the target area can be obtained based on water system distribution information, wherein the branch data information refers to relevant information affecting water system distribution, such as the flow, the flow direction, the area of the river, the number and the form of the branch, the density of the river network, the water system attribution, the terrain, the hydraulic engineering, the flood control facility and the like of all the river water systems in the target area. The hydraulic engineering is an engineering which is built for controlling and allocating surface water and underground water in the nature to achieve the purposes of removing harm and benefiting. The flood control facilities refer to policy methods and infrastructure for researching and taking various countermeasures and measures according to the flood law and the characteristics of flood disasters so as to prevent or alleviate the flood disasters and guarantee the social and economic development.
Step S500: constructing a hydrodynamic model based on the data information of each branch to obtain a hydrodynamic model database;
specifically, the distributed hydrodynamic model is a numerical method for performing flow field simulation based on computational fluid dynamics, and the hydrodynamic model is a mathematical model for describing the correlation between water flow stress and motion. The hydrodynamic model establishes a mathematical model according to a basic equation of fluid mechanics, and carries out numerical simulation on the dynamic process of flowing water. And constructing a water outlet power model based on the data information of each branch, and further obtaining a database for obtaining the water power model, wherein the database contains all information of all river systems in the target area, and mainly comprises the flow direction, the flow speed and the flow of each branch of the river system and the formation reasons of the branch, and the formation reasons comprise the terrain, the water flow stress condition and the like.
Step S600: obtaining a model calculation sequence according to the water system relation network and the hydrodynamic model database;
specifically, the model calculation sequence refers to a corresponding relationship sequence between a water system relationship network and a hydrodynamic model database during model calculation. And obtaining a calculation sequence of the river water system distributed power model based on the water system relation network and the hydrodynamic model database.
Step S700: obtaining distributed computing device information;
step S800: obtaining a computing device matching sequence according to the model computing sequence and the distributed computing device information, and establishing communication connection between the computer device and the corresponding hydrodynamic model;
step S900: calculating according to the matching sequence of the calculating equipment to obtain a water system calculating result;
specifically, the distributed computing device information refers to information of computing devices of the distributed hydrodynamic model of the river water system. And the computer equipment is in communication connection with the corresponding hydrodynamic model, and a computing equipment matching sequence can be obtained further based on the model computing sequence and the distributed computing equipment information. And on the basis of the model calculation sequence and the calculation equipment information of the distributed hydrodynamic model of the river water system, a calculation equipment matching sequence can be obtained, and further on the basis of the calculation equipment matching sequence, the hydrodynamic model and the node data relation set, comprehensive calculation is carried out to obtain a river water system calculation result. The river water system is intelligently calculated, the calculation effect and efficiency are improved, and the technical effects of economic and mental losses caused by insufficient flood control scheduling preparation work are reduced.
Step S1000: and obtaining flood prevention scheduling information according to the water system calculation result.
Specifically, flood prevention scheduling information can be obtained according to the water system calculation result, and the flood prevention scheduling information refers to information for preparing and formulating flood prevention scheduling work according to flood prevention emergency measures formulated by river water system specific information based on flood prevention requirements.
Further, in the step S200 of obtaining the water system distribution data set according to the water system distribution information, the embodiment of the present application further includes:
step S210: obtaining a first set of images, the first set of images including water system distribution information;
step S220: obtaining tributary boundary characteristics, and setting the tributary boundary characteristics as convolution characteristics;
step S230: sequentially carrying out feature traversal comparison on the first image set according to the convolution features to obtain feature comparison results;
step S240: obtaining tributary distribution information according to the feature comparison result;
step S250: obtaining tributary node information according to the tributary distribution information;
step S260: and acquiring the water system distribution data set according to the tributary node information and the tributary distribution information.
Specifically, the first image set is a set composed of image information of all river systems in the target area at different angles, and the first image set includes distribution information of all river systems in the target area, specifically includes all relevant information such as river system branch distribution, branch flow, flow speed, water level, and the like. Based on the first image set, a tributary boundary feature, that is, information such as the flow, the flow direction, the area of the watershed, the number of branches, and the form thereof, of each tributary of all the river systems in the target area can be obtained. The convolution can act as a "feature extractor" in machine learning. And setting the branch boundary features as convolution features, namely extracting branch boundary features, respectively performing feature traversal comparison on boundary feature information of each water system and branches thereof in each branch boundary feature in the first image set according to the branch boundary features to obtain corresponding obtained feature comparison results, and obtaining distribution information of each branch of the river system according to the feature comparison results. Further, node information of each tributary, that is, a connection point between each river system, can be obtained. And comprehensively analyzing the tributary node information and the tributary distribution information to obtain a data set of the distribution of each river water system in the target area. By analyzing and sorting the water system distribution information, a water system distribution data set is obtained, and a data basis is provided for river water system calculation.
Further, step S1000 in the embodiment of the present application further includes:
step S1010: obtaining historical rainfall runoff generating information;
step S1020: constructing a rainfall calculation model according to the historical rainfall runoff generating information and the water system hydrodynamic relation;
step S1030: embedding the rainfall calculation model into the hydrodynamic model to obtain a first embedded model;
step S1040: acquiring first rainfall information;
step S1050: inputting the first rainfall information into the first embedded model to obtain water system prediction information;
step S1060: and obtaining the flood prevention scheduling information according to the water system prediction information.
Specifically, runoff refers to the process of rainfall subtracting losses to net rain, wherein the rainfall losses include plant entrapment, infiltration, pooling and evaporation. The runoff yield is the part of the water which forms runoff due to rainfall. The runoff producing situation is quite complicated due to different geographical positions of the watersheds and different rainfall characteristics. The historical rainfall runoff generating information refers to the runoff generating information of the target area formed by rainfall in the past through channels such as data collection and arrangement. Rainfall runoff is influenced by many factors such as rainfall intensity, rainfall duration, soil humidity, ground coverage, plant interception, filling, rainfall evaporation and the like, and the condition is complex. The rainfall calculation model can be constructed by analyzing in combination with the relation between the historical rainfall runoff production information and the water power of the water system, and can intelligently analyze, calculate and predict the runoff quantity formed by rainfall in the target area. And embedding the rainfall calculation model into the hydrodynamic model, namely obtaining a water volume predicted value of runoff formed due to rainfall in the target area through the embedding model of the hydrodynamic model.
The first rainfall information refers to one-time rainfall information in the target area, and comprises all rainfall information such as rainfall intensity, rainfall time and the like. Inputting the first rainfall information into a water power model, namely the first embedded model, so that river water system prediction information formed by the first rainfall in the target area can be obtained. By embedding the rainfall calculation model into the hydrodynamic model, the rainfall output flow predicted value of the target area can be conveniently and rapidly obtained through the hydrodynamic model, and the technical effect of making corresponding flood control dispatching preparation in advance according to the predicted value is achieved.
Further, in the step S900 according to the embodiment of the present application, the calculating according to the calculating device matching sequence to obtain a water system calculation result further includes:
step S910: acquiring water system connection information according to the water system relation network and the tributary node information;
step S920: acquiring a node data relation set according to the water system connection information and the tributary data information, wherein the node data relation is a data relation between an upstream tributary and an inflow tributary in the water system connection information;
step S930: and calculating according to the hydrodynamic model and the node data relation set based on the computing equipment matching sequence to obtain the water system calculation result.
Specifically, information on the water system connection relationship can be obtained from the water system connection network and the node information between the branches, and further, a node data relationship set, which is a data relationship between the upstream branch and the inflowing branch in the water system connection information, can be obtained based on the water system connection information and the branch data information. And on the basis of the model calculation sequence and the calculation equipment information of the distributed hydrodynamic model of the river water system, a calculation equipment matching sequence can be obtained, and further on the basis of the calculation equipment matching sequence, the hydrodynamic model and the node data relation set, comprehensive calculation is carried out to obtain a water system calculation result. The river water system is intelligently calculated, the calculation effect and efficiency are improved, and the technical effects of economic and mental losses caused by insufficient flood control scheduling preparation work are reduced.
Further, the embodiment of the present application further includes:
step S1110: obtaining first branch flow information;
step S1120: obtaining first branch topographic information, first branch water depth information and first branch water flow speed information according to the first branch information and the data information of each branch;
step S1130: obtaining a first branch flow riverbed shearing force according to the first branch flow topographic information, the first branch flow water depth information and the first branch flow water velocity information;
step S1140: acquiring first branch flow ecological information;
step S1150: constructing a first branch flow ecological model according to the first branch flow ecological information and the shearing force of the first branch flow riverbed;
step S1160: obtaining a first hydrodynamic model according to the first branch flow information and the hydrodynamic model database;
step S1170: embedding the first shunt ecological model into the first hydrodynamic model to obtain a second embedded model;
step S1180: obtaining a first real-time ecology, the first real-time ecology having a first time;
step S1190: inputting the first real-time ecology into the second embedded model to obtain ecological water flow prediction information;
step S11100: and obtaining first branch scheduling information according to the ecological water flow prediction information.
Specifically, the first tributary information is basic information such as a flow direction, a flow rate, and a watershed area of any one tributary in the target region. The first branch terrain information refers to the feature shape and the landform condition information of the first branch; the water depth refers to the vertical distance from the free section of the water body to the surface of the river bed of the water body, and the water depth information of the first branch refers to the water depth information of the first branch; the first substream flow rate information refers to flow rate information of the first substream. And combining the first branch flow information and the data information of each branch flow to obtain first branch flow topographic information, water depth information and flow velocity information. Further, a bed shear force of the first substream, which is a force capable of causing shear deformation of the bed of the first substream, can be obtained.
The first tributary ecological information refers to the existing and developing state of the tributaries in the current natural environment, and includes information such as the flow rate, the flow direction, the number of the tributaries and the forms thereof. The water flow velocity and water depth distribution of the river bed have certain influence on the ecology of the river bed, meanwhile, the ecological environment of a river bank, namely a water bottom invertebrate, also has certain influence relation with the water flow velocity and the water power, and the relation between the hydrodynamic variable and the ecological parameter can be balanced, wherein the shearing force of the river bed is the most important hydrodynamic influence factor, the nonlinear horizontal transfer momentum equation is more accurately described by utilizing the distribution of the water flow depth, the speed and the shearing force, an area on a water flow curve can be converted into a calculation point by utilizing the method, then a two-dimensional and one-dimensional finite model is utilized to simulate or calculate the hydrodynamic variable, and the calculation amount can be reduced. According to the ecological information of the first branch stream and the shearing force of the riverbed of the first branch stream, an ecological model of the first branch stream can be constructed; combining the first tributary information and the hydrodynamic model database to obtain a hydrodynamic model of the first tributary; embedding the first bypass ecological model into the first hydrodynamic model to obtain a second embedded model of the first hydrodynamic model. The first hydrodynamic model embedded in the first tributary ecological model may intelligently obtain real-time ecological information of the first tributary, i.e., the first real-time ecology, which has a first time. And inputting the first real-time ecology into the second embedded model, namely the first hydrodynamic model, so as to obtain ecological water flow prediction information of the first branch, and further performing scheduling processing on the obtained prediction information, namely the first branch scheduling information. The real-time ecology of any tributary in the target area can be intelligently calculated and predicted, ecological water flow prediction can be carried out on any tributary, scheduling management can be carried out on the tributary in advance based on the prediction result, and the technical effects of intelligent calculation and real-time monitoring and management of the river channel water system are achieved.
Further, the rainfall calculation model includes evaporation calculation, output flow calculation, and confluence calculation, and step S1020 of the embodiment of the present application further includes:
step S1021: the evaporation calculation adopts a multilayer evaporation calculation mode, a calculation coefficient w of the branch evaporation capacity is input, model parameters are the water storage capacity and the evaporation coefficient of a first layer, a second layer and an Nth layer, and the evaporation capacity of the first layer, the second layer and the Nth layer is output, wherein N is a natural number larger than 2.
Specifically, the evaporation calculation adopts a multilayer evaporation calculation method, the rainfall is divided into N levels, wherein N is a natural number greater than 2, the evaporation capacity of the current level is calculated for each level, and the evaporation capacity of each level is the total evaporation capacity of the rainfall. Each level is automatically formed into an evaporation model, the evaporation capacity and the water storage capacity of rainfall in each level are different, and the calculation coefficient w of the branch evaporation capacity is input into the evaporation model of the corresponding level, so that the evaporation capacity of the first layer, the second layer and the Nth layer can be obtained. By the method for calculating the evaporation capacity in a layered mode, the calculation result of the rainfall evaporation capacity is more accurate, and the high accuracy of the model calculation result is improved.
Further, the embodiment of the present application further includes:
step 1210: acquiring rainfall prediction information within a first preset time;
step S1220: calculating through all hydrodynamic force models in the hydrodynamic force model database to obtain a tributary water conservancy information set based on the rainfall prediction information;
step S1230: obtaining a water system adjustment relation coefficient according to the water system relation network;
step S1240: inputting branch water conservancy information and the water system adjustment relation coefficient in the branch water conservancy information set into a water conservancy prediction model, wherein the water conservancy prediction model is obtained by training and converging a plurality of groups of training data, and each group of the plurality of groups of training data comprises the branch water conservancy information, the water system adjustment relation coefficient and identification information for identifying the water conservancy prediction information;
step S1250: obtaining an output result of the water conservancy prediction model, wherein the output result comprises the water conservancy prediction information, and water system prediction information is obtained based on the water conservancy prediction information of all branches in a water system;
step S1260: and obtaining flood prevention scheduling information according to the water system prediction information, the hydraulic engineering and the flood prevention facilities.
Specifically, the first predetermined time refers to a certain period of time during which a precipitation situation needs to be predicted. The rainfall prediction information in the first preset time refers to specific information about rainfall in a certain time period predicted by the hydrodynamic model, and the specific information includes rainfall amount, rainfall duration and other prediction information. And calculating all hydrodynamic force models in the hydrodynamic force model database based on rainfall prediction information to obtain a tributary water conservancy information set, wherein the tributary water conservancy information refers to the situation that various measures are manually taken due to the needs of survival and development to control and allocate the tributaries so as to prevent and control the flood and drought disasters and develop, utilize and protect water resources. A water system adjustment relation coefficient can be obtained according to the water system relation network, and the water system adjustment relation coefficient refers to the adjustment relation factor of the branch in the water system relation network.
The water conservancy prediction model is a neural network model, namely a neural network model in machine learning, reflects many basic characteristics of human brain functions, and is a highly complex nonlinear dynamic learning system. The method can continuously carry out self-training learning according to training data, each group of data in the multiple groups of training data comprises branch water conservancy information, the water system adjustment relation coefficient and identification information for identifying water conservancy prediction information, the water conservancy prediction model is continuously corrected by self, and when the output information of the water conservancy prediction model reaches a preset accuracy rate/convergence state, the supervised learning process is finished. By carrying out data training on the water conservancy prediction model, the water conservancy prediction model can process input data more accurately, and further the output result of the water conservancy prediction model is more accurate, so that the technical effects of accurately obtaining data information and improving the intellectualization of the evaluation result are achieved.
Further, according to the water system prediction information, the hydraulic engineering and the flood control facilities, corresponding flood control scheduling information can be obtained. The flood prevention scheduling information refers to information for preparing and formulating flood prevention scheduling work according to historical flood prevention scheduling measures.
Further, step S1240 in the embodiment of the present application further includes:
step S1241: acquiring tributary hydraulic engineering information;
step S1242: acquiring tributary influence information according to the tributary hydraulic engineering information;
step S1243: inputting the branch influence information into the water conservancy prediction model to obtain water conservancy influence prediction information;
step S1244: obtaining first loss data by analyzing data loss of the water conservancy influence prediction information;
step S1245: and inputting the first loss data into the water conservancy prediction model for training to obtain an incremental water conservancy prediction model, wherein the incremental water conservancy prediction model is a new model generated after incremental learning of the water conservancy prediction model.
Specifically, the tributary hydraulic engineering information refers to the situation that various measures are manually taken for survival and development, and the tributaries are controlled and allocated to prevent and treat water and drought disasters, develop, utilize and protect water resources. According to tributary hydraulic engineering information, tributary influence information can be obtained, and the tributary influence information refers to the influence of the tributary on the formation of the tributary due to the hydraulic engineering condition of the tributary. And inputting the tributary influence information into a water conservancy prediction model to obtain water conservancy influence prediction information. Furthermore, data loss analysis is carried out on the water conservancy influence prediction information, first loss data can be obtained, the first loss data are input into the water conservancy prediction model to be trained, and an incremental water conservancy prediction model can be obtained. The incremental water conservancy prediction model is a water conservancy prediction model obtained by machine learning based on first loss data characteristics of the plurality of branches, and because difference characteristic data need to be combined with old training data of the water conservancy prediction model to complete a comprehensive incremental learning result, basic performance of the water conservancy prediction model can be reserved after the first loss data are subjected to incremental learning, corresponding incremental learning is completed, and the incremental water conservancy prediction model is an updated model after the incremental learning, so that the technical effects of performing the incremental learning on newly added characteristics and improving the updating performance of the prediction model are achieved.
To sum up, the calculation method and the system for the distributed hydrodynamic model of the river water system provided by the embodiment of the application have the following technical effects:
1. obtaining water system distribution information; acquiring a water system distribution data set according to the water system distribution information; acquiring a water system relation network according to the water system distribution data set; obtaining data information of each branch according to the water system distribution information, wherein the data information of each branch comprises water flow, topography, water depth, hydraulic engineering and flood control facilities; constructing a hydrodynamic model based on the data information of each branch to obtain a hydrodynamic model database; obtaining a model calculation sequence according to the water system relation network and the hydrodynamic model database; obtaining distributed computing device information; obtaining a computing device matching sequence according to the model computing sequence and the distributed computing device information, and establishing communication connection between the computer device and the corresponding hydrodynamic model; calculating according to the matching sequence of the calculating equipment to obtain a water system calculating result; and obtaining flood prevention scheduling information according to the water system calculation result. The flood prevention dispatching method has the advantages that flood prediction with high speed and high precision is achieved, the technical effect of an effective and reasonable flood prevention dispatching scheme is provided, and the flood prevention dispatching work arrangement is given enough time for relevant departments.
2. Through the water conservancy prediction model established on the basis of the neural network model, continuous self-training learning can be carried out according to training data, and through carrying out data training on the water conservancy prediction model, the water conservancy prediction model is more accurate in processing input data, so that the output result of the water conservancy prediction model is more accurate, the accurate data information acquisition is achieved, and the intelligent technical effect of the evaluation result is improved.
Example two
Based on the method for calculating the distributed hydrodynamic model of the river water system in the foregoing embodiment, the present invention also provides a system for calculating the distributed hydrodynamic model of the river water system, referring to fig. 2, where the system includes:
the first obtaining unit 11: the first obtaining unit is used for obtaining water system distribution information;
the second obtaining unit 12: the second obtaining unit is used for obtaining a water system distribution data set according to the water system distribution information;
the third obtaining unit 13: the third obtaining unit is used for obtaining a water system relation network according to the water system distribution data set;
the fourth obtaining unit 14: the fourth obtaining unit is used for obtaining data information of each branch according to the water system distribution information, wherein the data information of each branch comprises water flow, topography, water depth, hydraulic engineering and flood control facilities;
the fifth obtaining unit 15: the fifth obtaining unit is used for constructing a hydrodynamic model based on the data information of each tributary to obtain a hydrodynamic model database;
the sixth obtaining unit 16: the sixth obtaining unit is configured to obtain a model calculation sequence according to the water system relationship network and the hydrodynamic model database;
the seventh obtaining unit 17: the seventh obtaining unit is configured to obtain distributed computing device information;
the eighth obtaining unit 18: the eighth obtaining unit is configured to obtain a computing device matching sequence according to the model computing sequence and the distributed computing device information, and the computer device establishes a communication connection with a corresponding hydrodynamic model;
ninth obtaining unit 19: the ninth obtaining unit is used for calculating according to the calculating equipment matching sequence to obtain a water system calculating result;
tenth obtaining unit 20: and the tenth obtaining unit is used for obtaining flood prevention scheduling information according to the water system calculation result.
Further, the system further comprises:
an eleventh obtaining unit: the eleventh obtaining unit is configured to obtain a first image set including water system distribution information;
a twelfth obtaining unit: the twelfth obtaining unit is configured to obtain a tributary boundary feature, and set the tributary boundary feature as a convolution feature;
a thirteenth obtaining unit: the thirteenth obtaining unit is configured to perform feature traversal comparison on the first image set in sequence according to the convolution features to obtain a feature comparison result;
a fourteenth obtaining unit: the fourteenth obtaining unit is configured to obtain tributary distribution information according to the feature comparison result;
a fifteenth obtaining unit: the fifteenth obtaining unit is configured to obtain tributary node information according to the tributary distribution information;
a sixteenth obtaining unit: the sixteenth obtaining unit is configured to obtain the water system distribution data set according to the tributary node information and the tributary distribution information.
Further, the system further comprises:
a seventeenth obtaining unit: the seventeenth obtaining unit is used for obtaining historical rainfall runoff generating information;
a first building unit: the first construction unit is used for constructing a rainfall calculation model according to the historical rainfall runoff generating information and the water system hydrodynamic relation;
an eighteenth obtaining unit: the eighteenth obtaining unit is configured to embed the rainfall calculation model into the hydrodynamic model to obtain a first embedded model;
a nineteenth obtaining unit: the nineteenth obtaining unit is used for obtaining first rainfall information;
a twentieth obtaining unit: the twentieth obtaining unit is configured to input the first rainfall information into the first embedded model to obtain water system prediction information;
a twenty-first obtaining unit: the twenty-first obtaining unit is configured to obtain the flood prevention scheduling information according to the water system prediction information.
Further, the system further comprises:
a twenty-second obtaining unit: the twenty-second obtaining unit is used for obtaining water system connection information according to the water system relation network and the tributary node information;
a twenty-third obtaining unit: the twenty-third obtaining unit is configured to obtain a node data relationship set according to the water system connection information and the tributary data information, where a node data relationship is a data relationship between an upstream tributary and an inflow tributary in the water system connection information;
a twenty-fourth obtaining unit: the twenty-fourth obtaining unit is configured to perform calculation according to the hydrodynamic model and the node data relationship set based on the computing device matching sequence, and obtain the water system calculation result.
Further, the system further comprises:
a twenty-fifth obtaining unit: the twenty-fifth obtaining unit is configured to obtain first branch stream information;
a twenty-sixth obtaining unit: the twenty-sixth obtaining unit is configured to obtain first branch topographic information, first branch water depth information, and first branch flow velocity information according to the first branch flow information and the branch flow data information;
a twenty-seventh obtaining unit: the twenty-seventh obtaining unit is configured to obtain a first lateral flow riverbed shearing force according to the first lateral flow topographic information, the first lateral flow water depth information, and the first lateral flow water velocity information;
a twenty-eighth obtaining unit: the twenty-eighth obtaining unit is configured to obtain first branch stream ecological information;
a second building element: the second construction unit is used for constructing a first branch flow ecological model according to the first branch flow ecological information and the shearing force of the first branch flow riverbed;
a twenty-ninth obtaining unit: the twenty-ninth obtaining unit is configured to obtain a first hydrodynamic model according to the first branch flow information and the hydrodynamic model database;
a thirtieth obtaining unit: the thirtieth obtaining unit is configured to embed the first bypass ecological model into the first hydrodynamic model, and obtain a second embedded model;
a thirty-first obtaining unit: the thirty-first obtaining unit is configured to obtain a first real-time ecology, where the first real-time ecology has a first time;
a thirty-second obtaining unit: the thirty-second obtaining unit is used for inputting the first real-time ecology into the second embedded model to obtain ecological water flow prediction information;
a thirty-third obtaining unit: the thirty-third obtaining unit is configured to obtain first branch flow scheduling information according to the ecological water flow prediction information.
Further, the system further comprises:
a first output unit: the first output unit is used for calculating the distribution by adopting a multilayer evaporation calculation mode, inputting a calculation coefficient w of branch evaporation capacity, outputting the evaporation capacity of the first layer, the second layer and the nth layer by using model parameters including water storage capacity and evaporation coefficient of the first layer, the second layer and the nth layer, wherein N is a natural number greater than 2.
Further, the system further comprises:
a thirty-fourth obtaining unit: the thirty-fourth obtaining unit is used for obtaining rainfall prediction information in a first preset time;
a thirty-fifth obtaining unit: the thirty-fifth obtaining unit is used for calculating and obtaining a tributary water conservancy information set through all hydrodynamic force models in the hydrodynamic force model database based on the rainfall prediction information;
a thirty-sixth obtaining unit: the thirty-sixth obtaining unit is used for obtaining a water system adjustment relation coefficient according to the water system relation network;
a thirty-seventh obtaining unit: the thirty-seventh obtaining unit is configured to input the branch water conservancy information and the water system adjustment relation coefficient in the branch water conservancy information set into a water conservancy prediction model, where the water conservancy prediction model is obtained by training convergence through multiple sets of training data, and each of the multiple sets of training data includes the branch water conservancy information, the water system adjustment relation coefficient, and identification information identifying the water conservancy prediction information;
a thirty-eighth obtaining unit: the thirty-eighth obtaining unit is configured to obtain an output result of the water conservancy prediction model, where the output result includes the water conservancy prediction information, and obtain water system prediction information based on the water conservancy prediction information of all branches in a water system;
a thirty-ninth obtaining unit: and the thirty-ninth obtaining unit is used for obtaining flood control scheduling information according to the water system prediction information, the hydraulic engineering and the flood control facilities.
Further, the system further comprises:
a fortieth obtaining unit: the fortieth obtaining unit is used for obtaining branch hydraulic engineering information;
forty-first obtaining unit: the forty-first obtaining unit is used for obtaining tributary influence information according to the tributary hydraulic engineering information;
a forty-second obtaining unit: the forty-second obtaining unit is used for inputting the tributary influence information into the water conservancy prediction model to obtain water conservancy influence prediction information;
a forty-third obtaining unit: the forty-third obtaining unit is used for carrying out data loss analysis on the water conservancy influence prediction information to obtain first loss data;
a forty-fourth obtaining unit: the forty-fourth obtaining unit is configured to input the first loss data into the water conservancy prediction model for training, and obtain an incremental water conservancy prediction model, where the incremental water conservancy prediction model is a new model generated after incremental learning of the water conservancy prediction model.
In the present description, the embodiments are described in a progressive manner, and each embodiment focuses on differences from other embodiments, the calculation method and specific example based on a distributed hydrodynamic model of a river water system in the first embodiment of fig. 1 are also applicable to the calculation system based on a distributed hydrodynamic model of a river water system in this embodiment, and through the foregoing detailed description of the calculation method and system based on a distributed hydrodynamic model of a river water system, it is clear to those skilled in the art that the calculation system based on a distributed hydrodynamic model of a river water system in this embodiment is not described in detail here for the sake of brevity of the description. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Exemplary electronic device
The electronic device of the embodiment of the present application is described below with reference to fig. 3.
Fig. 3 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.
Based on the inventive concept of the method for calculating a distributed hydrodynamic model of a river water system in the foregoing embodiments, the invention further provides a system for calculating a distributed hydrodynamic model of a river water system, wherein a computer program is stored thereon, and when being executed by a processor, the computer program implements the steps of any one of the methods described above.
Where in fig. 3 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 305 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other apparatus over a transmission medium.
The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
The application provides a calculation method of a distributed hydrodynamic model of a river water system, which is applied to a calculation system of the distributed hydrodynamic model of the river water system, wherein the method comprises the following steps: acquiring water system distribution information; acquiring a water system distribution data set according to the water system distribution information; acquiring a water system relation network according to the water system distribution data set; obtaining data information of each branch according to the water system distribution information, wherein the data information of each branch comprises water flow, topography, water depth, hydraulic engineering and flood control facilities; constructing a hydrodynamic model based on the data information of each branch to obtain a hydrodynamic model database; obtaining a model calculation sequence according to the water system relation network and the hydrodynamic model database; obtaining distributed computing device information; obtaining a computing device matching sequence according to the model computing sequence and the distributed computing device information, and establishing communication connection between the computer device and the corresponding hydrodynamic model; calculating according to the matching sequence of the calculating equipment to obtain a water system calculating result; and obtaining flood prevention scheduling information according to the water system calculation result. The method solves the technical problem that in the prior art, accurate forecasting and reasonable flood prevention scheduling schemes cannot be rapidly provided, so that relevant departments do not have enough time to make decisions and take measures, and further the economic and even life safety of people is greatly threatened. The method achieves the aim of rapid development of the computer technology at present, the specific situation of a river system is comprehensively considered by utilizing a distributed hydrodynamic model, the calculation method is improved, high-precision measurement and calculation values are intelligently given, meanwhile, a reasonable flood prevention scheduling scheme is given, the flood prediction with high speed and high precision is achieved, the technical effect of the effective and reasonable flood prevention scheduling scheme is provided, and the arrangement of the flood prevention scheduling work in enough time of relevant departments is given.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, the present application may take the form of an entirely software embodiment, an entirely hardware embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application is in the form of a computer program product that may be embodied on one or more computer-usable storage media having computer-usable program code embodied therewith. And such computer-usable storage media include, but are not limited to: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk Memory, a Compact Disc Read-Only Memory (CD-ROM), and an optical Memory.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction system which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A method for calculating a distributed hydrodynamic model of a river water system, wherein the method comprises the following steps:
acquiring water system distribution information;
acquiring a water system distribution data set according to the water system distribution information;
acquiring a water system relation network according to the water system distribution data set;
obtaining data information of each branch according to the water system distribution information, wherein the data information of each branch comprises water flow, topography, water depth, hydraulic engineering and flood control facilities;
constructing a hydrodynamic model based on the data information of each branch to obtain a hydrodynamic model database;
obtaining a model calculation sequence according to the water system relation network and the hydrodynamic model database;
obtaining distributed computing device information;
obtaining a computing device matching sequence according to the model computing sequence and the distributed computing device information, and establishing communication connection between the computer device and the corresponding hydrodynamic model;
calculating according to the matching sequence of the calculating equipment to obtain a water system calculating result;
and obtaining flood prevention scheduling information according to the water system calculation result.
2. The method of claim 1, wherein the obtaining a water system profile data set from the water system profile information comprises:
obtaining a first set of images, the first set of images including water system distribution information;
obtaining tributary boundary characteristics, and setting the tributary boundary characteristics as convolution characteristics;
sequentially carrying out feature traversal comparison on the first image set according to the convolution features to obtain feature comparison results;
obtaining tributary distribution information according to the feature comparison result;
obtaining tributary node information according to the tributary distribution information;
and acquiring the water system distribution data set according to the tributary node information and the tributary distribution information.
3. The method of claim 1, wherein the method comprises:
obtaining historical rainfall runoff generating information;
constructing a rainfall calculation model according to the historical rainfall runoff generating information and the water system hydrodynamic relation;
embedding the rainfall calculation model into the hydrodynamic model to obtain a first embedded model;
acquiring first rainfall information;
inputting the first rainfall information into the first embedded model to obtain water system prediction information;
and obtaining the flood prevention scheduling information according to the water system prediction information.
4. The method of claim 2, wherein said performing a calculation in accordance with said computing device matching sequence to obtain a water-based calculation comprises:
acquiring water system connection information according to the water system relation network and the tributary node information;
acquiring a node data relation set according to the water system connection information and the tributary data information, wherein the node data relation is a data relation between an upstream tributary and an inflow tributary in the water system connection information;
and calculating according to the hydrodynamic model and the node data relation set based on the computing equipment matching sequence to obtain the water system calculation result.
5. The method of claim 1, wherein the method comprises:
obtaining first branch flow information;
obtaining first branch topographic information, first branch water depth information and first branch water flow speed information according to the first branch information and the data information of each branch;
obtaining a first branch flow riverbed shearing force according to the first branch flow topographic information, the first branch flow water depth information and the first branch flow water velocity information;
acquiring first branch flow ecological information;
constructing a first branch flow ecological model according to the first branch flow ecological information and the shearing force of the first branch flow riverbed;
obtaining a first hydrodynamic model according to the first branch flow information and the hydrodynamic model database;
embedding the first shunt ecological model into the first hydrodynamic model to obtain a second embedded model;
obtaining a first real-time ecology, the first real-time ecology having a first time;
inputting the first real-time ecology into the second embedded model to obtain ecological water flow prediction information;
and obtaining first branch scheduling information according to the ecological water flow prediction information.
6. The method of claim 3, wherein the rainfall calculation model comprises an evaporation calculation, a production flow calculation, a confluence calculation;
the distribution calculation adopts a multilayer evaporation calculation mode, a calculation coefficient w of the branch evaporation capacity is input, model parameters are the water storage capacity and the evaporation coefficient of a first layer, a second layer and an Nth layer, and the evaporation capacity of the first layer, the second layer and the Nth layer is output, wherein N is a natural number larger than 2.
7. The method of claim 1, wherein the method comprises:
acquiring rainfall prediction information within a first preset time;
calculating through all hydrodynamic force models in the hydrodynamic force model database to obtain a tributary water conservancy information set based on the rainfall prediction information;
obtaining a water system adjustment relation coefficient according to the water system relation network;
inputting branch water conservancy information and the water system adjustment relation coefficient in the branch water conservancy information set into a water conservancy prediction model, wherein the water conservancy prediction model is obtained by training and converging a plurality of groups of training data, and each group of the plurality of groups of training data comprises the branch water conservancy information, the water system adjustment relation coefficient and identification information for identifying the water conservancy prediction information;
obtaining an output result of the water conservancy prediction model, wherein the output result comprises the water conservancy prediction information, and water system prediction information is obtained based on the water conservancy prediction information of all branches in a water system;
and obtaining flood prevention scheduling information according to the water system prediction information, the hydraulic engineering and the flood prevention facilities.
8. The method of claim 7, wherein the method comprises:
acquiring tributary hydraulic engineering information;
acquiring tributary influence information according to the tributary hydraulic engineering information;
inputting the branch influence information into the water conservancy prediction model to obtain water conservancy influence prediction information;
obtaining first loss data by analyzing data loss of the water conservancy influence prediction information;
and inputting the first loss data into the water conservancy prediction model for training to obtain an incremental water conservancy prediction model, wherein the incremental water conservancy prediction model is a new model generated after incremental learning of the water conservancy prediction model.
9. A computing system for a distributed hydrodynamic model of a river water system, wherein the system comprises:
a first obtaining unit: the first obtaining unit is used for obtaining water system distribution information;
a second obtaining unit: the second obtaining unit is used for obtaining a water system distribution data set according to the water system distribution information;
a third obtaining unit: the third obtaining unit is used for obtaining a water system relation network according to the water system distribution data set;
a fourth obtaining unit: the fourth obtaining unit is used for obtaining data information of each branch according to the water system distribution information, wherein the data information of each branch comprises water flow, topography, water depth, hydraulic engineering and flood control facilities;
a fifth obtaining unit: the fifth obtaining unit is used for constructing a hydrodynamic model based on the data information of each tributary to obtain a hydrodynamic model database;
a sixth obtaining unit: the sixth obtaining unit is configured to obtain a model calculation sequence according to the water system relationship network and the hydrodynamic model database;
a seventh obtaining unit: the seventh obtaining unit is configured to obtain distributed computing device information;
an eighth obtaining unit: the eighth obtaining unit is configured to obtain a computing device matching sequence according to the model computing sequence and the distributed computing device information, and the computer device establishes a communication connection with a corresponding hydrodynamic model;
a ninth obtaining unit: the ninth obtaining unit is used for calculating according to the calculating equipment matching sequence to obtain a water system calculating result;
a tenth obtaining unit: and the tenth obtaining unit is used for obtaining flood prevention scheduling information according to the water system calculation result.
10. A computing system for a distributed hydrodynamic model of a river water system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of any one of claims 1 to 8 when executing the program.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113639805A (en) * | 2021-10-14 | 2021-11-12 | 成都万江港利科技股份有限公司 | Flow measurement method based on channel section flow velocity field reconstruction |
| CN116823231A (en) * | 2023-08-25 | 2023-09-29 | 中关村科学城城市大脑股份有限公司 | River channel water level information generation method and device, electronic equipment and readable medium |
| CN117273313A (en) * | 2023-09-08 | 2023-12-22 | 中关村科学城城市大脑股份有限公司 | Water network regulation method, device, electronic equipment and computer readable medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007063849A (en) * | 2005-08-31 | 2007-03-15 | Toshiba Corp | Method of creating river water level prediction model, device for predicting river water level, and program for creating river water level prediction model |
| CN102289570A (en) * | 2011-07-23 | 2011-12-21 | 浙江大学 | Flood forecast method based on rainfall-runoff-flood routing calculation |
| CN107451716A (en) * | 2017-06-28 | 2017-12-08 | 宁波市水利水电规划设计研究院 | A kind of flood control decision support method, electronic equipment, storage medium and system |
| CN108388957A (en) * | 2018-01-25 | 2018-08-10 | 河海大学 | A kind of middle and small river Flood Forecasting Method and its forecast system based on multiple features fusion technology |
| US20190354873A1 (en) * | 2018-02-16 | 2019-11-21 | Lucas Pescarmona | Analysis system and hydrology management for basin rivers |
-
2021
- 2021-06-07 CN CN202110633899.0A patent/CN113392489B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007063849A (en) * | 2005-08-31 | 2007-03-15 | Toshiba Corp | Method of creating river water level prediction model, device for predicting river water level, and program for creating river water level prediction model |
| CN102289570A (en) * | 2011-07-23 | 2011-12-21 | 浙江大学 | Flood forecast method based on rainfall-runoff-flood routing calculation |
| CN107451716A (en) * | 2017-06-28 | 2017-12-08 | 宁波市水利水电规划设计研究院 | A kind of flood control decision support method, electronic equipment, storage medium and system |
| CN108388957A (en) * | 2018-01-25 | 2018-08-10 | 河海大学 | A kind of middle and small river Flood Forecasting Method and its forecast system based on multiple features fusion technology |
| US20190354873A1 (en) * | 2018-02-16 | 2019-11-21 | Lucas Pescarmona | Analysis system and hydrology management for basin rivers |
Non-Patent Citations (1)
| Title |
|---|
| 陈会峰: "河南省山丘区小流域洪水预报系统研究及应用", 《人民黄河》, no. 07, 10 July 2013 (2013-07-10), pages 20 - 22 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113639805A (en) * | 2021-10-14 | 2021-11-12 | 成都万江港利科技股份有限公司 | Flow measurement method based on channel section flow velocity field reconstruction |
| CN116823231A (en) * | 2023-08-25 | 2023-09-29 | 中关村科学城城市大脑股份有限公司 | River channel water level information generation method and device, electronic equipment and readable medium |
| CN116823231B (en) * | 2023-08-25 | 2023-11-24 | 中关村科学城城市大脑股份有限公司 | River channel water level information generation method and device, electronic equipment and readable medium |
| CN117273313A (en) * | 2023-09-08 | 2023-12-22 | 中关村科学城城市大脑股份有限公司 | Water network regulation method, device, electronic equipment and computer readable medium |
| CN117273313B (en) * | 2023-09-08 | 2024-05-24 | 中关村科学城城市大脑股份有限公司 | Water network regulation method, device, electronic equipment and computer readable medium |
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