55 results about "Flood flow" patented technology

The invention belongs to the technical field of data processing, and discloses an LSTM neural network cycle hydrological forecasting method based on mutual information, which comprises the following steps: screening and classifying original data through mutual information analysis, and taking rainfall, reservoir water level and flow hydrological characteristics as input characteristics of a long-term and short-term memory cycle forecasting model; the long-term change of flood is reflected by simulating rainfall process training and determining the structure of the LSTMC model; and verifying the output of the model by using the actual flood data. According to the method, the data set is analyzed by adopting a mutual information-based method, the flow at the current moment and each hydrological characteristic of the previous longer time period are fully captured, and the input characteristics of the model are dynamically selected. According to the method, the deep learning algorithm is utilized, the cyclic prediction model based on the LSTM neural network is adopted, when the method is used for flood flow time series prediction, the problem that the hydrological change process is greatly influenced by factors in the earlier stage is solved, and effective features can be automatically captured well.

The invention discloses a real-time flood forecasting intelligent model forecasting method for medium and small rivers. The method comprises the steps: firstly collecting historical hydrological dataof all stations of a research basin, and storing the historical hydrological data into a hydrological historical database; secondly, performing data cleaning, data conversion and data set division onhydrological history data; thirdly, constructing a three-stage real-time flood forecasting model. In the first stage, a data driving model based on a support vector machine is used for forecasting flood. In the second stage, a Markov method is adopted to intelligently adjust the state of the initial forecasting model. In the third stage, a historical flood flow mode the same as the historical flood flow mode in the real-time flood process is searched in a flood mode library. After that, the overall form of the flood hydrograph forecasted in real time is adjusted. The performance of the intelligent model is evaluated by using the test set data. Finally, real-time forecasts are made. The method has the advantages that the flood peak precision and the flood trend can be effectively forecasted, and the method is an effective tool for real-time forecasting of flood of medium and small rivers.

The invention discloses a method for flood two-dimensional and three-dimensional dynamic display by using a river channel actually measured water level. A data processing tool provided by an ageographic information platform ArcGis is used, and the method comprises the following steps of 1, cross section arrangement monitoring; 2, river DEM production; 3, grid surface element manufacturing; 4, gridterrain interpolation; 5, grid water depth interpolation at each moment; 6, temporal data manufacturing; 7, flood dynamic display. According to the method, a traditional river channel water level display mode is completely changed, combined display of water level data can be achieved, and after the flood data is superimposed on a topographic map, an aerial image and a DEM, the display effect is more vivid and is like real flood flowing on a river channel; conditions, such as the water surface width change, water depth distribution and the flood peak position, are clear at a glance in the display process, so that decision-making departments are assisted in mastering the overall dynamic conditions of flood more visually, and the development purpose of the water conservancy informatization technology is achieved.

The invention relates to a self-adaptive cofferdam lake gradual collapse coupling prediction model which is characterized by comprising the following steps: fitting a cofferdam lake water level-reservoir capacity curve to obtain the total water volume W0 of a reservoir area before dam collapse; deciding a breach width bm and a breach depth hm; calculating a dam break maximum flow of the dam site section to obtain the reservoir capacity Wm corresponding to the break depth hm; calculating the average volume sand content percentage p; calculating the maximum water depth ratio [beta]m of the dam break position; calculating an expansion duration tau; calculating a real-time dam break flow process q(t), and calculating a drainage amount W(tau); checking whether the product is in an acceptable range; calculating duration T after the dam break flood peak; deducing a post-peak flow process; calculating the residual water quantity W(T) in front of the dam; checking whether the product is in an acceptable range; and integrating the obtained pre-peak and post-peak flow processes q(t). According to the method, the possible maximum flood peak flow can be obtained, the dam break flood process can be deduced together, the dam break flood flow process can be quickly obtained, and a reference is provided for front-line emergency rescue treatment.

The invention discloses a damsite flood restoration method based on a Copula function. A joint distribution function of damsite peak flow before a reservoir is built, computative reservoir-in peak flow and peak flow time is constructed according to the Copula function, a joint distribution function of damsite flood volume, commutative reservoir-in flood volume and peak occurring time is constructed, a most probable value function of the damsite peak flow and the damsite flood volume is derived on the basis of the conditional probability density maximum principle of the joint distribution function, reservoir-in flood data after the reservoir is built is substituted into the most probable value function, a most probable value of the damsite peak flow and the damsite flood volume is solved, and therefore reservoir-in flood volume process data after the reservoir is built are restored to damsite flood. According to the damsite flood restoration method based on the Copula function, a strong statistic basis is achieved, the compound mode of the damsite flood and reservoir-in flood is unique, and the characteristics of an actual measurement sample can be objectively reflected; the internal relatedness among all the characteristic quantities are fully considered, and a reference basis which is important and strong in operability can be supplied to the reservoir to restore the damsite flood according to the reserivoir-in flood data.

The invention provides an electric power facility flood disaster risk assessment method considering reservoir influence, and the method comprises the following steps: obtaining the rainfall intensityand rainfall space distribution condition of a mountain torrent ditch basin according to the rainfall data of the basin where an electric power facility is located, and employing a Gunn Bell extreme value method for calculation to obtain the rainfall frequency; calculating the flood flow according to the rainfall intensity of the basin where the electric power facilities are located and the collected reservoir information; substituting the flood flow data as an important input field into a rainstorm flood inundation model together with terrain and land utilization data for flood inundation evolution process simulation to obtain inundation water depth and area space distribution conditions of a drainage basin where the power facilities are located; and according to the flood inundation water depth and the flood inundation range of the disaster area or actually measured hydrological data, carrying out simulation precision analysis on the inundation water depth and area by utilizing the disaster situation matching rate. By considering the flood influence of the reservoir on the downstream drainage basin, rainstorm flood disaster risk assessment is further carried out more comprehensively.

The invention discloses a deep learning model for predicting flood flow features on flood flow paths. The deep learning model receives structural features of each point on the blood flow vector paths,physiological features of humans and personal features, and outputs the blood flow features of each point on the blood flow vector paths. The deep learning model comprises a support vector machine; and after the structure features of each point on the blood flow vector paths, the physiological features of humans and the personal features are input to the support vector machine, blood flow features of each point on the blood flow vector paths are obtained through calculation. The deep learning model integrates the structural features of blood vessels, physiological features and personal features of users, so that the blood flow features on the blood flow vector paths can be accurately predicted.

The invention belongs to the technical field of basin design flood derivation, and particularly relates to a non-consistent design flood calculation method considering influence of flood season dispersity. The non-consistent design flood calculation method comprises the following steps of: constructing a flood hyper-quantitative series POT; analyzing seasonal distribution characteristics of the flood in the year according to the over-quantitative series POT of the flood; constructing a POT flood probability distribution model by combining the flood flow magnitude sequence model and the flood intra-year occurrence frequency sequence model according to a flood seasonal test result; selecting the annual population Kt as a potential human activity indirect factor, and establishing a mathematical model between the Kt and statistical parameters of the flood flow magnitude sequence and the flood annual occurrence frequency sequence; and substituting the established statistical parameter mathematical model into the POT flood probability distribution model, and calculating a non-uniform design flood value according to a specified recurrence period of flood control requirements. According tothe non-consistent design flood calculation method, the defect that the flood calculation result designed based on the POT hyper-quantitative sequence is too large or too small is overcome to a certain extent, and support is provided for basin flood risk scheduling and management.

The invention discloses an optical microangiography image segmentation and evaluation method. Based on optical coherence tomography (OCT), unmarked and three-dimensional optical microangiography needs to split a dynamic flood flow signal from a static organization background so as to realize three-dimensional radiography of a capillary. In the invention, ''a random phase vector'', a statistical optical model and a difference algorithm of optical microangiography (comprising an amplitude difference and a complex signal difference) are combined so that a signal statistics theory model of the optical microangiography is firstly derived and a statistics characteristic difference of the dynamic flood flow signal and the static organization background is successfully interpreted, wherein the statistics characteristic difference of the dynamic flood flow signal and the static organization background is a contrast source of the microangiography. Therefore, an automatic threshold segmentation algorithm based on a minimum segmentation error rate and an objective evaluation standard based on a residual segmentation error rate are proposed.

The invention discloses a dam bursting flood analysis system of a dam system. The dam bursting flood analysis system comprises a topology analysis module of the dam system, a data collection module, asingle-dam analysis module, a flood evolution analysis module and a prediction module; the topology analysis module of the dam system is used for determining the grade of dams in the dam system; thedata collection module is used for collecting information of the dams in the dam system; the single-dam analysis module is used for establishing water level models of the dams, and determining burst inundation state models of the dams are determined according to the water level models of the dams and building parameter data of dam bodies; the flood evolution analysis module is used for analyzing the process that flood flows from the low-grade dams to the high-grade dams, and calculating the inflow amount of the downstream high-grade dams according to the outflow amount of the low-grade dams; and the prediction module is used for predicating whether burst of the downstream dams is caused by dam burst in the flood evolution process or not and predicating the burst time of the downstream burst dams and the flood peak flow of burst flood.

The invention discloses a flood flow prediction system and method based on deep learning. A station end sends single-end original rainfall data and original flow data to a prediction end; the prediction end obtains single-end sending data, prior rainfall data in the future P hours and original position information of N hydrological stations; preprocesses the original rainfall data, the prior rainfall data, the original flow data and the original position information; forms gridding rainfall data based on the processed rainfall data, the processed prior rainfall data and the processed positioninformation; extracts spatial distribution characteristics of the gridding rainfall data, and extracting time sequence characteristics of the rainfall data in historical T hours and future P hours toobtain a first output characteristic; for the processed flow data, extracts a time sequence characteristic of the flow data in historical T hours to obtain a second output characteristic; and performsmerging classification prediction on the first output feature and the second output feature to obtain a flow prediction value of the target hydrological station in the future P hours.

The invention discloses a torrential flood flow calculating method based on the virtual reservoir breaking process. Based on the intercoupling relationship among hydrodynamics, soil mechanics and sediment dynamics and through combination with contributions, neglected in calculation in the past, of the depression water storage mount, the soil water content and the like to the flow, the method comprises the steps that each hydrogeomorphic unit of the slope surface is assumed as a virtual reservoir, the torrential flood flow is divided into the slope surface runoff and the virtual reservoir breaking effusive flow, a comprehensive solving algorithm of the slope surface hydrologic process and the sediment erosion process is established, the state change of runoff generation and confluence of the slope surface before and after the critical state is controlled by taking the critical starting velocity as the control condition, the slope surface erosion process of torrential flood is calculatedthrough a hyperbolic scouring formula, the effusive flow is calculated accordingly, and then the effusive flow is superimposed with the slope surface runoff volume of the hydrogeomorphic units of theslope surface to obtain the total flow of the torrential flood. The calculating method has the definite physical mechanism, the scientificity of researching of the torrential flood physical process and the accuracy of flow calculating are improved, and technical support is provided for torrential flood disaster analysis and early warning work.

The invention discloses a flood flow prediction method, and belongs to the field of deep learning. The method comprises the following steps: 1, inputting a collected past flood session data set of the Changhua region, and extracting data of the input data set; 2, transmitting the data into a feature enhancement module, enlarging the dimension difference of input and output data by rewriting a multi-level convolutional neural network, and highlighting and obtaining key information in flood factors; 3, a feature extraction module and a time information coding module are introduced into the recurrent neural network, modeling is performed from different perspectives, and enhanced data are transmitted into the constructed neural network for training; 4, balancing the double-view-angle weight, adjusting the proportion of the double-view-angle weight, and carrying out perception information fusion through a merging unit to complete training; and 5, predicting the test set data to obtain a final prediction result. The prediction method is high in accuracy and high in prediction efficiency, and flood prediction can be rapidly completed.

The invention relates to yao bath powder special for gynecology. The yao bath powder is a powder composition prepared by mixing, by weight, 1-2 parts of sargentgloryvine stems, 0.2-2 parts of caulis spatholobi, 0.2-2 parts of akebia stems, 0.2-2 parts of radix rubiae, 0.2-2 parts of sambucus adnata and 0.2-2 parts of coarse morinda howiana, and raw medicine powder of one or more garden balsam stems, bitter peach leaves, sweet wormwood herb and spire treebine stems can be added. The yao bath powder is boiled in boiled water for 3-5 minutes to obtain soup or brewed with hot water to obtain the soup, and then the soup is added with cold water to adjust the temperature to 35-45 DEG C for naked soak bath. The yao bath powder has the effects of conducting antisepsis and anti-inflammation, relieving swelling, removing stasis, regulating vital energy, promoting flood flow, restoring menstrual flow, enriching the blood and the like, and has remarkable effects on gynecological diseases such as irregular menstruation, dysmenorrhea, lower abdomen pendant expansion and edema in the gestation period or the woman body health care such as restoring the postpartum birth canal, clearing fire, relieving pain, clearing heat and relieving itching. The yao bath powder is prepared from pure vegetable drug, contains no chemical agents, and is free of toxins, harm and side effects, drawn materials are cheap, cost is low, the selling price conforms to the consumption ability of the masses, and popularization is easy.

The invention relates to hydroelectric generating plants which may be prefabricated and subsequently exchanged for preexisting radial water control gates. The hydroelectric generating plant disclosed herein may be particularly advantageous for hydroelectric development of projects with preexisting submergible radial gates. Various configurations are disclosed which maximize generating capacity, hydraulic efficiency, and flood flow capacity, while minimizing weight and cost.

A flood and sewage flow distributing system for ecologically purifying domestic sewage comprises a drainage groove (1), a flood draining groove (2), a drainage hole (3) and a flow distributing dam (4). The drainage groove (1) is in the shape of an inverted trapezoid, and an inlet of the drainage groove (1) is wide while an outlet of the drainage groove (1) is narrow; water stopping walls (5) are arranged on two sides and at the bottom of the drainage groove (1), the flow distributing dam (4) is located between the water stopping wall on one side of the drainage groove (1)and the water stopping wall at the bottom of the drainage groove (1), the flow distributing dam (4), the water stopping wall on one side of the drainage groove (1) and the water stopping wall at the bottom of the drainage groove (1) form a triangle, and the flood draining groove (2) is formed in an area among the flow distributing dam (4) and the water stopping walls (5); the diameter of the drainage hole (3) is 0.15m; a sand stopping screen (6) is mounted at an outlet end of the drainage hole (3), a filter screen is circular, the aperture of meshes is 0.002m, a grid screen (7) is mounted at an inlet end of the drainage hole (3) and is circular, the diameter of the grid screen (7) is 0,15m, and the aperture of grids is 0,02m; and the flow distributing dam (4) is required to be higher than the upper edge of the drainage hole by 0,2m, and is higher than the stopping wall of a water outlet of the flood draining groove by 0,2m. The flood and sewage flow distributing system is simple and reasonable in structure, low in manufacturing cost and high in popularization and application values, and can be widely applied to various domestic sewage ecological purifying systems.

The invention discloses a small watershed short-term flood forecasting method based on a typical design flood hydrograph. The small watershed short-term flood forecasting method comprises the following steps: S1, obtaining design flood peak flow and the typical design flood hydrograph of a small watershed river channel in different years; s2, judging whether the riverway starts to perform short-term flood forecasting or not according to the actual measurement flow; s3, determining the forecasting time of short-term flood forecasting according to the actually measured flood flow of the riverway; s4, determining a slope Kn according to the typical design flood hydrograph of the corresponding age limit; s5, determining the predicted flood flow q'n + 1 at the moment tn + 1 according to the actually measured flood flow qn and the slope Kn at the moment tn; s6, judging whether short-term flood forecasting can be ended or not according to the actually measured flood flow at the moment tn + 1;s7, correcting the age limit Tn of the design flood hydrograph for calculating the slope Kn according to the actually measured flood flow qn + 1 at the moment tn + 1 and the predicted flood flow q'n+ 1 at the moment tn + 1; and S8, ending the short-term flood forecasting. Compared with an existing flow algorithm and a corresponding water level method, the method has the advantages of being simple, rapid and the like.

The invention provides a river peak flood flow range calculation method, and the method comprises the steps of obtaining multi-year rainfall monitoring data and weather forecast of a research area, and further comprises the following steps: calculating the average moving speed of a rainfall center of the research area; constructing a plurality of rainfall processes in different moving directions; and calculating the flood peak flow range of the river section through the flood model. The invention provides a river peak discharge range calculation method which mainly solves the problem that when rainfall forecast data of a research area is obtained, the uncertainty of rainfall center movement possibly causes the inaccurate peak discharge calculation result. According to the invention, the method comprises the steps: designing various possible rainfall center moving directions, calculating the flood peak flow in various moving directions, extracting the maximum value and the minimum value of the flood peak flow in the calculation result, i.e., the possible flood peak flow range, which can provide a more scientific reference basis for river risk evaluation.

The invention discloses a river way flood flow evolution rule simulating method based on a wolves algorithm. The river way flood flow evolution rule simulating method based on the wolves algorithm comprises the following steps: step 1, establishing a Muskingum model by taking minimum river way flood actual flow process error; step 2, calibrating parameters of the Muskingum model in the step 1 by using the wolves algorithm to obtain a flow routing coefficient when errors of a river way flood flow simulating process and an actual flow process are minimum; and step 3, substituting the flow routing coefficient obtained in the step 2 into the Muskingum model in the step 1 to obtain a calibrated Muskingum model objective function. According to the river way flood flow evolution rule simulating method based on the wolves algorithm, the wolves algorithm needs to be introduced to calibrate the parameters of the Muskingum model, effectiveness, feasibility and superiority of the wolves algorithmin calibration on parameters of a flood evolution model, and the river way flood flow evolution rule simulating method based on the wolves algorithm has important practical significance and application value on improvement of forecast accuracy of three elements and arriving time of flood and prevention of flood damage.

The invention discloses a pipeline suspension failure prediction method under flood action. The method comprises the steps of setting a value of a suspension coefficient of a pipeline; calculating a flood hydrograph of a river through which the pipeline passes; according to the flood hydrograph, calculating the change relation of the flood speed along with time; calculating the change relation ofthe pipeline suspension length along with time according to the suspension coefficient of the pipeline; performing finite element modeling on the basis of the change relation of the flood speed alongwith time and the change relation of the pipeline suspension length along with time, calculating the change rule of the mechanical behavior of the pipeline along with time through time-history analysis, and predicting the yield time of the pipeline. According to the method, the change relation between the suspension length of the pipeline and the flood flow rate along with time is calculated by utilizing the set suspension coefficient and the obtained flood hydrograph, modeling is carried out in finite element analysis by utilizing the relation, and the yield time of the pipeline is predicted,so that the emergency time is obtained.

The invention discloses a flood flow prediction method of a sequential network based on a self-attention mechanism, and belongs to the technical field of flood flow prediction. The method comprises the following steps: 1, preprocessing historical flood data including flood flow and related flood characteristic factors; 2, constructing a flood prediction model in parallel by using a time convolutional network and a long-short-term memory network; 3, setting related hyper-parameters of the flood prediction model; 4, training the flood prediction model by using the historical flood data, and storing a final model; and 5, applying the trained model to flood prediction, and evaluating a result according to a corresponding index. The prediction method provided by the invention has better robustness, has higher accuracy compared with a traditional long-short-term memory network prediction method, and can effectively complete flood flow prediction of middle and small river basins.

The invention discloses a water flow prediction method and device based on machine learning, and electronic equipment. The method comprises the steps of obtaining original rainfall data and original flow data of a predetermined drainage basin; carrying out preprocessing to obtain processed rainfall data and processed flow data respectively; constructing input data based on the processed rainfall data, the processed flow data and the known rainfall data of each hydrological station in the future P hours; inputting the input data into a pre-trained flood flow prediction model to perform loop iteration prediction, extracting time sequence features from the input data of the iteration and performing classification prediction during each iteration to obtain a flow prediction value of the targethydrological station in the next hour, and using the obtained flow prediction value in the next hour to reconstruct input data for iteration of the next hour in the future until P times of iterationare completed, and thus obtaining a flow prediction value of the target hydrological station in the next P hours; according to the invention, the flood flow condition in a future time period can be accurately predicted.

The invention discloses a hydrological multi-model time-varying weight combination forecasting method, and the method comprises the following steps: determining a plurality of hydrological models participating in combination forecasting, and obtaining each piece of hydrometeorological data in each historical flood session of a target watershed; calculating a weight value of a single hydrological model at each moment in each historical flood by using a Bayesian model averaging algorithm; screening out each preferred flood sample most similar to the current flood; selecting k flood samples with the highest matching degree with the current flood by using a KNN method, obtaining a forecast weight value of each hydrological model through the idea of inverse distance weighting, and carrying out weighted summation by combining the flood flow forecast values of each hydrological model at the forecast moment to obtain a fused flood flow forecast value of the target drainage basin. And forecasting of the flood flow of the target drainage basin is realized. According to the method, the multiple hydrological models are fused and forecasted through the Bayesian theory, updating combination of the time-varying weights is achieved with the help of the KNN learning algorithm, the precision of the flood forecast value is improved, and a basis is provided for flood control decision making.

The invention aims to provide an HTTP flood attack defense method and system. An HTTP 302 redirection principle is used, the attack and the normal request are identified by verifying the legality of the returned message of the client; a normal user can receive and return a correct verification code to the defense equipment for verification, and the attack tool does not have the function of responding to a redirection message or returning the correct verification code, so that the HTTP Flood flow in the mixed flow can be completely filtered, and the use of the normal user is not hindered.

The invention discloses a joint emergency dispatching method for a cascade reservoir group. The joint emergency dispatching method comprises the steps that operation conditions of two dispatching reservoirs are firstly monitored, then corresponding out-reservoir flow constraint conditions are determined according to different combinations of dangerous conditions, outburst or normal operation of the two dispatching reservoirs, and then discharge capacity states, inflow states and in-reservoir flood flow in each period of time of the two dispatching reservoirs are determined; and finally, a trial algorithm is adopted to forward deduce and solve a water balance formula for the outflow state variables in each period of time to determine the out-reservoir flood flow and the corresponding waterstorage capacity of the two dispatching reservoirs in each period of time. The joint emergency dispatching method combines hydraulic connection between units of the cascade reservoir group in a drainage basin, gives full play to the regulating function of the reservoirs and the associated reservoirs upstream and downstream, and solves the emergency dispatching problem of extraordinary water volumein specific situations from the perspective of prevention; and risk dispatching plans of different dispatching modes are formed, and decision support is provided for relevant reservoir safety administrative departments and reservoir management units.

The invention discloses an irregular river cross-section flow measurement device. The device comprises a display terminal, a support frame, a cable and a sensor, the support frame is arranged along the bank of a river, the display terminal is arranged on the support frame, the display terminal is connected with the sensor through the cable, the sensor is located at the side of the river, the support frame comprises a first landing leg, a support platform, a bracket, a second landing leg connecting plate, a displacement connecting strip and a second landing leg, the first landing leg is provided with a first landing leg oval hole, the second landing leg is provided with a second landing leg oval hole, the first landing leg, the bracket and the support platform are of a integrally connectedstructure, one end of the displacement connecting strip is located in the second landing leg oval hole, and the other end of the displacement connecting strip is connected with the bracket or locatedin the first landing leg oval hole. According to the irregular river cross-section flow measurement device, hydrometry data can be rapidly and accurately obtained, and flood discharge data of the river can be collected rapidly in the great floods.

The invention discloses a flood flow prediction method and device based on deep learning, and electronic equipment. The method comprises the steps of obtaining original rainfall data, original flow data and original position information of a hydrological station; preprocessing the original rainfall data, the prior rainfall data, the original flow data and the original position information to obtain processed rainfall data, processed flow data and processed position information; forming gridding rainfall data based on the processed rainfall data, the processed prior rainfall data and the processed position information; extracting spatial distribution characteristics of the gridding rainfall data, and extracting time sequence characteristics of the rainfall data in historical T hours and future P hours to obtain a first output characteristic; for the processed flow data, extracting a time sequence characteristic of the flow data in historical T hours to obtain a second output characteristic; and performing merging classification prediction on the first output feature and the second output feature to obtain a flow prediction value of the target hydrological station in the future P hours.

The invention relates to a transferring device, in particular to a flood flowing direction transferring device for irrigation and water conservancy. According to the technical aim to be achieved, flood or mass-flow water can be transferred and drained without being drained into farmland to inundate rice, and rice growth is benefited. According to the technical scheme, the flood flowing direction transferring device for irrigation and water conservancy comprises a cross rod, a supporting rod, a semi-arc-shaped pipeline, a protruding block, a drainage pipe and the like; the drainage pipe is mounted at the left end of the cross rod, a water supply pipe is mounted at the right end of the cross rod, the supporting rod is mounted in the middle of the top of the cross rod, and the semi-arc-shapedpipeline is rotationally mounted at the top end of the supporting rod. By means of a supporting device, the semi-arc-shaped pipeline can be supported, when a large amount of water is needed in farmland, the water is drained into the farmland, and the effects of being capable of transferring and draining the flood or the mass-flow water without draining the flood or the mass-flow water into the farmland to inundate the rice and not influencing rice growth are achieved.