CN117057616A - Water conservancy monitoring method and system based on digital twin - Google Patents
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Abstract
The invention discloses a digital twin-based water conservancy monitoring method and system, which relate to the technical field of water conservancy monitoring, wherein rainfall conditions in a monitoring area are monitored, a rainfall condition set is established, a rainfall condition coefficient is generated, if the rainfall condition set is larger than a condition threshold value, current flood related parameters are collected in a first sampling area, a first water surface parameter set is established after summarization, and a first risk coefficient is generated; setting a data acquisition point in a second sampling area, acquiring current flood state parameters, and establishing a second risk coefficient; generating a comprehensive risk coefficient by the first risk coefficient and the second risk coefficient, and establishing a digital twin water conservancy model covering the monitoring area; and carrying out simulation analysis on the flood change in the monitoring area to obtain the flood characteristics in the monitoring area, and matching with a corresponding flood drainage strategy. And compared with monitoring the flood risk through single data acquisition or monitoring equipment, the flood risk monitoring system has wider coverage range.
Description
Technical Field
The invention relates to the technical field of water conservancy monitoring, in particular to a water conservancy monitoring method and system based on digital twinning.
Background
Digital twinning is a virtual model or representation that digitally replicates and emulates an entity, process, system or product in the real world. The technology connects a physical entity with a digital model, and through real-time data synchronization and interaction, digital twinning can reflect the state and change of the real world. It has wide application in various fields such as manufacturing industry, energy, traffic, city planning, medical treatment, etc. For example, the manufacturing industry may create digital twins of a product for monitoring and optimizing a production process.
In the Chinese patent of the invention with the application number of 202110382116.6, the invention discloses a water conservancy monitoring method and system based on digital twinning, after the sensing data of a water conservancy site acquired by a current sensor are obtained, the sensing data are processed by a digital twinning reasoning model, so that the state data of the water conservancy site are obtained, the acquisition precision and efficiency of the running state of the water conservancy site are improved, and the labor cost is reduced; and after the state data of the water conservancy site is obtained, the running state of the water conservancy site is further presented in a visual mode by the digital twin display model, so that a user can intuitively obtain the running state of the water conservancy site, and the user experience is improved.
The above application is mainly focused on displaying the running state data of the water conservancy site, however, under the condition that the water conservancy site is in a rainfall-holding condition, the ground water level rises, the saturation of soil increases, when the water body can not be rapidly discharged or can not permeate into the ground, the risk of flood can be greatly increased, the existing water conservancy monitoring system is focused on monitoring the running state of the current water conservancy site, and the current possible flood risk is difficult to judge and evaluate, so that the corresponding protection means are not beneficial to be selected to reduce the flood influence, and the larger effect is difficult to play.
Therefore, the invention provides a water conservancy monitoring method and system based on digital twinning.
Disclosure of Invention
(one) solving the technical problems
Aiming at the defects of the prior art, the invention provides a digital twinning-based water conservancy monitoring method and a digital twinning-based water conservancy monitoring system, which are characterized in that a rainfall condition set is established and a rainfall condition coefficient is generated by monitoring rainfall conditions in a monitoring area, if the rainfall condition set is larger than a condition threshold value, current flood related parameters are collected in a first sampling area, a first water surface parameter set is established after summarizing, and a first risk coefficient is generated; setting a data acquisition point in a second sampling area, acquiring current flood state parameters, and establishing a second risk coefficient; generating a comprehensive risk coefficient by the first risk coefficient and the second risk coefficient, and establishing a digital twin water conservancy model covering the monitoring area; and carrying out simulation analysis on the flood change in the monitoring area to obtain the flood characteristics in the monitoring area, and matching with a corresponding flood drainage strategy. The comprehensive judgment and monitoring of the flood risk in the monitoring area are wider in coverage range and solve the problems in the background technology compared with the monitoring of the flood risk through single data acquisition or monitoring equipment.
(II) technical scheme
In order to achieve the above purpose, the invention is realized by the following technical scheme:
the digital twinning-based water conservancy monitoring method comprises the following steps of,
if the monitoring area is in a continuous rainfall state, determining the area where the water conservancy site is located as a monitoring area, setting monitoring points in the monitoring area, monitoring rainfall conditions in the monitoring area, establishing a rainfall condition set according to a monitoring result, generating a rainfall condition coefficient Jsx according to the rainfall condition set, and if the rainfall condition coefficient Jsx is larger than a condition threshold, sending first early warning information to the outside;
wherein, the rainfall condition coefficient Jsx is generated by the rainfall condition set, and the specific method is as follows: after dimensionless treatment is carried out on the accumulated rainfall Lv and the ground water level rising speed Dv, the method is according to the following formula:
wherein, the meaning of the parameter is:and->The specific value of the weight coefficient can be set by user adjustment or obtained by mathematical analysis software through simulation analysis;
if the acquired rainfall condition coefficient Jsx is larger than a preset condition threshold value, sending early warning information to the outside;
after receiving the first early warning information, selecting a first sampling area in a monitoring area, collecting current flood related parameters in the first sampling area, establishing a first water surface parameter set after summarizing, generating a first risk coefficient Oxs by the first water surface parameter set, and sending out first alarm information if the first risk coefficient Oxs is higher than a first risk threshold;
After receiving the first alarm information, selecting a second sampling area in the monitoring area, setting a data acquisition point in the second sampling area, acquiring current flood state parameters, summarizing and establishing a second water surface parameter set, establishing a second risk coefficient Txs by the second water surface parameter set, and sending out second alarm information if the second risk coefficient Txs is higher than a second risk threshold;
if the first alarm information and the second alarm information are not received, generating a comprehensive risk coefficient based on the first risk coefficient Oxs and the second risk coefficient TxsAnd predicting by adopting a function fitting and secondary smooth index prediction method, and obtaining a predicted value ++of the weighted average>The method comprises the steps of carrying out a first treatment on the surface of the If the comprehensive risk coefficient->Predicted value of +.>If the comprehensive risk threshold is exceeded, a digital twin water conservancy model covering the monitoring area is established, and the digital twin water conservancy model is marked as a monitoring water conservancy digital twin model;
and taking rainfall and evaporation as independent variables for input, carrying out simulation analysis on flood change in a monitoring area by using a monitoring water conservancy digital twin model, and if flood characteristics in the monitoring area are obtained through prediction, matching corresponding flood drainage strategies from a pre-established flood drainage strategy library, and outputting or outputting the flood drainage strategies after correction.
Further, after determining the areas where a plurality of water conservancy stations are located, determining the areas as monitoring areas, establishing an electronic map at least covering the monitoring areas, and setting monitoring points in the adjacent areas with the water conservancy stations;
if the current rainfall state is in the monitoring area and the current daily average rainfall is larger than the contemporaneous historical average value, continuously monitoring the underground water level and the rainfall process at the monitoring point, at least respectively obtaining the current accumulated rainfall Lv, and if the underground water level changes, obtaining the underground water level rising speed and determining the rising speed as the underground water level rising speed Dv;
and after the accumulated rainfall Lv and the ground water level rising speed Dv are summarized, a rainfall condition set is established.
Further, after receiving the first early warning information, randomly selecting a plurality of first sampling areas in the monitoring area, and collecting data in the first sampling areas through the collecting device, wherein the data to be collected comprises: acquiring the ground water level depth along a fixed time interval, if the ground water level of the first sampling area is continuously changed, acquiring the average increasing speed of the ground water level, and acquiring the ground water level rising speed Sv after analysis; identifying the water area coverage area in the first sampling area, and if the water area coverage area is changed, analyzing and acquiring the average increasing speed of the water area coverage area to generate the water area increasing speed Mv; and after the water level rising speed Sv of the ground and the area increasing speed Mv of the water area are summarized, a first water surface parameter set is established.
Further, the first risk coefficient Oxs of the flood is generated by the first water surface parameter set, and the specific generation mode is as follows:
dimensionless processing is carried out on the water level rise speed Sv and the area rise speed Mv, historical average values of the water level rise speed Sv and the area rise speed Mv are respectively obtained, and a first risk coefficient Oxs is generated according to the following formula:
wherein,is the historical mean value of the water level rising speed Sv, < >>Is the historical mean value of area acceleration Mv, +.>Is->Is a weight coefficient, and->And->P is any positive integer between 3 and 6;
and if the acquired first risk coefficient Oxs is higher than the first risk threshold, sending out first alarm information.
Further, after receiving the first alarm information, a second sampling area is set at a position adjacent to the first sampling area in the monitoring area, and the current flooding state is acquired in the second sampling area, specifically as follows:
setting a plurality of data acquisition points with certain intervals in a second sampling area, and detecting the current state of soil at the data acquisition points to obtain the soil saturation Bd of the current soil; if the water body at or near the data acquisition point is in a flowing state, acquiring the water body flow velocity Ld; randomly selecting a plurality of data acquisition points, detecting and acquiring the accumulation and silt quantity at the points, further acquiring the accumulation speed of silt, and generating the accumulation and silt speed Ys; and (3) summarizing the soil saturation Bd, the water flow rate Ld and the silt accumulation speed Ys, and then establishing a second water surface parameter set.
Further, the second risk coefficient Txs of the flood is generated by the second water surface parameter set, and the specific generation mode is as follows:
after carrying out dimensionless treatment on the soil saturation Bd, the water flow rate Ld and the silt accumulation speed Ys, the method comprises the following steps:
the significance of the parameters is:and->，/>The specific value of the weight coefficient can be adjusted and set by a user, and can also be obtained by mathematical analysis software through simulation analysis;
and if the acquired second risk coefficient Txs is higher than the second risk threshold, sending out second alarm information.
Further, when the first alarm information and the second alarm information are not received, a plurality of first risk coefficients Oxs and second risk coefficients Txs are continuously obtained, and a comprehensive risk coefficient is generated by the first risk coefficient Oxs and the second risk coefficient TxsThe specific mode is as follows:
wherein,and->By comprehensive risk factors->And (3) characterizing flood risks in the monitoring area, wherein the characterization mode is as follows:
wherein,for the weight, its specific value can be set by the user adjustment, +.>Is the expected mean value of the first risk factor Oxs, < >>N is a positive integer greater than 1, which is the expected mean of the second risk factor Txs.
Further, a plurality of comprehensive risk coefficientsArranged along a time axis, fitted functionally according to its trend, marked ++after K-S test >Prediction function, by->Prediction function versus comprehensive risk factor>Predicting to generate a predicted value as a first prediction coefficient +.>The method comprises the steps of carrying out a first treatment on the surface of the According to a secondary smooth index prediction method, the comprehensive risk coefficientForming a prediction, generating a second prediction coefficient +.>；
The comprehensive risk coefficient is generated as followsRisk prediction value ++>；
Wherein,are all weight coefficients +.>The specific value of which can be set by the user;
if the risk coefficient is integratedRisk prediction value ++>Acquiring an electronic map which at least covers a monitoring area when the comprehensive risk threshold is exceeded, and marking the topographic features of the monitoring area and the existing flood discharge measures on the electronic map;
using the marked electronic map and environmental condition parameters in the monitored area, and the current water surface parameters of the flood covered area; based on the Bp neural network model, combining the parameters, after training and testing, establishing a digital twin water conservancy model covering the monitoring area, and marking the digital twin water conservancy model as the monitoring water conservancy digital twin model.
Further, at least obtaining rainfall and evaporation capacity of water in a monitoring area, setting a prediction period, taking the rainfall and the evaporation capacity as input independent variables, performing simulation analysis on flood variation in the monitoring area by using a monitoring water conservancy digital twin model, and obtaining coverage area, average depth and water flow of a water body in the monitoring area after at least one prediction period;
The method comprises the steps of collecting existing drainage strategies through linear retrieval on line or off line, building a drainage strategy library after summarizing, taking the coverage area and depth flow of the predicted water body as flood characteristics, matching corresponding drainage strategies from the drainage strategy library according to the correspondence between the flood characteristics and the drainage strategies, and outputting the drainage strategies;
at least taking a drainage strategy and rainfall as input independent variables, performing simulation analysis by using a monitoring water conservancy digital twin model drainage strategy, judging whether the water coverage area and the average depth in a monitoring area are reduced after the drainage strategy is executed, namely verifying whether the drainage strategy is effective, and outputting the drainage strategy if the drainage strategy is effective;
if the drainage strategy is invalid, various condition parameters of the drainage strategy, such as the flood discharge direction, the positions and the number of newly opened flood discharge channels and the like, are adjusted until the drainage strategy is valid, and the corrected drainage strategy is output.
A digital twinning-based water conservancy monitoring system comprising:
the monitoring unit is used for determining the area where the water conservancy site is located as a monitoring area if the monitoring area is in a continuous rainfall state, setting monitoring points in the monitoring area, monitoring rainfall conditions in the monitoring area, establishing a rainfall condition set according to a monitoring result, generating a rainfall condition coefficient Jsx according to the rainfall condition set, and sending first early warning information to the outside if the rainfall condition coefficient Jsx is larger than a condition threshold;
The first evaluation unit selects a first sampling area in the monitoring area after receiving the first early warning information, collects current flood related parameters in the first sampling area, establishes a first water surface parameter set after summarizing, generates a first risk coefficient Oxs from the first water surface parameter set, and sends out first alarm information if the first risk coefficient is higher than a first risk threshold;
the second evaluation unit selects a second sampling area in the monitoring area after receiving the first alarm information, sets a data acquisition point in the second sampling area, acquires current flood state parameters, gathers and establishes a second water surface parameter set, establishes a second risk coefficient Txs by the second water surface parameter set, and sends out second alarm information if the second risk coefficient Txs is higher than a second risk threshold;
the model building unit generates a comprehensive risk coefficient based on the first risk coefficient Oxs and the second risk coefficient Txs if the first alarm information and the second alarm information are not receivedAnd predicting by adopting a function fitting and secondary smooth index prediction method, and obtaining a predicted value ++of the weighted average>The method comprises the steps of carrying out a first treatment on the surface of the If the comprehensive risk coefficient->Predicted value of +.>If the comprehensive risk threshold is exceeded, a digital twin water conservancy model covering the monitoring area is established, and the digital twin water conservancy model is marked as a monitoring water conservancy digital twin model;
And the scheme matching unit takes rainfall and evaporation as independent variables for input, the monitoring water conservancy digital twin model carries out simulation analysis on the flood change in the monitoring area, and if the flood characteristics in the monitoring area are obtained through prediction, the corresponding flood drainage strategy is matched from a pre-established flood drainage strategy library and is output or is output after correction.
(III) beneficial effects
The invention provides a water conservancy monitoring method and system based on digital twinning, which have the following beneficial effects:
1. after the monitoring area is in a continuous rainfall state, a first water surface parameter set is acquired and established in a first sampling area, a first risk coefficient Oxs is generated, the flood state in the monitoring area is tracked and judged, and if the monitoring area is displayed to have the flood risk based on the change of the water level and the water area, first alarm information is sent out; personnel in the monitoring area can avoid danger in time after receiving the first alarm information.
2. If the water cannot be discharged in time, the water flow rate Ld and the silt accumulation speed Ys are associated together, the influence degree of the flood risk is estimated from the angle of the water flow rate, comprehensive judgment is carried out on the flood risk in the monitoring area, and an administrator in the monitoring area can select a corresponding protection means according to the current water state change, so that the flood influence is reduced through the execution of monitoring.
3. At present, no flood risk exists, and the comprehensive risk coefficient is obtainedAnd predicting the flood risk, so as to predict whether the flood risk possibly exists in the monitoring area, if so, establishing a monitoring water conservancy digital twin model according to the current various condition parameters in the monitoring area, carrying out simulation analysis and prediction on the flood risk and the change thereof in the monitoring area, and realizing comprehensive judgment and monitoring on the flood risk in the monitoring area.
4. By predicting the following weather conditions, judging whether the flood risk is generated in the monitoring area, after the monitoring effect is realized, the prediction effect on the flood risk in the monitoring area can be realized, and if rainfall still exists in the monitoring area, the risk of the monitoring area can be reduced, and the potential safety hazard brought by the monitoring area is reduced;
5. after flood characteristics and a pre-built flood drainage strategy library are obtained, the corresponding flood drainage strategy is rapidly matched after flood risks exist, and the feasibility of the flood drainage strategy is verified and corrected by combining simulation analysis; and when the flood risk is possibly generated, the corresponding drainage strategy is rapidly acquired, and the efficiency of formulating the drainage strategy is improved, so that the flood risk can be rapidly processed, and the occurrence of larger potential safety hazards is avoided.
Drawings
FIG. 1 is a schematic flow chart of a digital twin-based water conservancy monitoring method;
fig. 2 is a schematic structural diagram of the digital twin-based water conservancy monitoring system.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides a digital twin-based water conservancy monitoring method, which comprises the following steps:
step one, if the monitoring area is in a continuous rainfall state, determining the area where the water conservancy site is located as a monitoring area, setting monitoring points in the monitoring area, monitoring rainfall conditions in the monitoring area, establishing a rainfall condition set according to monitoring results, generating a rainfall condition coefficient Jsx according to the rainfall condition set, and if the rainfall condition coefficient Jsx is larger than a condition threshold, sending first early warning information to the outside;
the first step comprises the following steps:
Step 101, after determining the areas where a plurality of water conservancy stations are located, determining the areas as monitoring areas, establishing an electronic map at least covering the monitoring areas, marking the positions of the water conservancy stations on the electronic map, and setting monitoring points in the adjacent areas with the water conservancy stations;
102, continuously monitoring the ground water level and the precipitation process at a monitoring point if the current rainfall state is in a monitoring area and the current daily average rainfall is greater than 120% of the contemporaneous historical average value, and acquiring the ground water level rising speed if the ground water level changes, and determining the ground water level rising speed as the ground water level rising speed Dv;
after the accumulated rainfall Lv and the ground water level rising speed Dv are summarized, a rainfall condition set is established;
step 103, generating a rainfall condition coefficient Jsx by a rainfall condition set, wherein the specific method is as follows: after dimensionless treatment is carried out on the accumulated rainfall Lv and the ground water level rising speed Dv, the method is according to the following formula:
wherein, the meaning of the parameter is:and->The specific value of the weight coefficient can be adjusted and set by a user, and can also be obtained by mathematical analysis software through simulation analysis;
if the acquired rainfall condition coefficient Jsx is larger than a preset condition threshold value, sending early warning information to the outside;
In use, the contents of steps 101 and 102 are combined:
after the monitoring area is determined by the water conservancy site, if the monitoring area is in a continuous rainfall state and the rainfall exceeds the historical average value, the monitoring area is likely to have a flood risk, at this time, the rainfall condition coefficient Jsx is generated by data collected at the monitoring point, whether the monitoring area has the flood risk is judged, and if the flood risk currently exists, early warning information can be timely sent out so that an administrator can process the flood risk in time.
Step two, after receiving the first early warning information, selecting a first sampling area in a monitoring area, collecting current flood related parameters in the first sampling area, establishing a first water surface parameter set after summarizing, generating a first risk coefficient Oxs by the first water surface parameter set, and sending out first alarm information if the first risk coefficient Oxs is higher than a first risk threshold;
the second step comprises the following steps:
step 201, after receiving the first early warning information, randomly selecting a plurality of first sampling areas in the monitoring area, and performing data acquisition in the first sampling areas through an acquisition device, wherein the data to be acquired includes:
acquiring the ground water level depth along a fixed time interval, if the ground water level of the first sampling area is continuously changed, acquiring the average increasing speed of the ground water level, and acquiring the ground water level rising speed Sv after analysis; identifying the water area coverage area in the first sampling area, and if the water area coverage area is changed, analyzing and acquiring the average increasing speed of the water area coverage area to generate the water area increasing speed Mv;
After the water level rising speed Sv of the ground and the area increasing speed Mv of the water area are summarized, a first water surface parameter set is established;
step 202, generating a first risk coefficient Oxs of the flood from the first water surface parameter set, wherein the specific generation mode is as follows:
dimensionless processing is carried out on the water level rise speed Sv and the area rise speed Mv, historical average values of the water level rise speed Sv and the area rise speed Mv are respectively obtained, and a first risk coefficient Oxs is generated according to the following formula:
wherein,is the historical mean value of the water level rising speed Sv, < >>Is the historical mean value of area acceleration Mv, +.>Is->Is a weight coefficient, and->And->P is any positive integer between 3 and 6;
if the obtained first risk coefficient Oxs is higher than the first risk threshold, it is indicated that there is a risk of flood, and management personnel are required to process in time, and at this time, first alarm information can be sent out.
In use, the contents of steps 201 and 202 are combined:
after the monitoring area is in a continuous rainfall state, a first water surface parameter set is acquired and established in a first sampling area, a first risk coefficient Oxs is generated, the flood state in the monitoring area is tracked and judged from the angles of water level rising and water area change, and if the change of the water level and the water area change shows that the flood risk exists in the monitoring area, first alarm information is sent out; personnel in the monitoring area can avoid danger in time after receiving the first alarm information.
Step three, after receiving the first alarm information, selecting a second sampling area in the monitoring area, setting a data acquisition point in the second sampling area, acquiring current flood state parameters, summarizing and establishing a second water surface parameter set, establishing a second risk coefficient Txs by the second water surface parameter set, and sending out second alarm information if the second risk coefficient Txs is higher than a second risk threshold;
the third step comprises the following steps:
step 301, after receiving the first alarm information, in order to reduce the risk of erroneous judgment, it needs to be verified, a second sampling area is set at a position adjacent to the first sampling area in the monitoring area, and the current flooding state is collected in the second sampling area, which specifically includes the following steps:
setting a plurality of data acquisition points with certain intervals in a second sampling area, and detecting the current state of soil at the data acquisition points to obtain the soil saturation Bd of the current soil; if the water body at or near the data acquisition point is in a flowing state, acquiring the water body flow velocity Ld;
if the flowing water body carries sediment or other suspended matters and floaters, randomly selecting a plurality of data acquisition points, detecting and acquiring the sediment accumulation amount at the points, further acquiring the accumulation speed of the sediment, and generating the sediment accumulation speed Ys;
The soil saturation Bd, the water flow rate Ld and the silt accumulation speed Ys are summarized, and a second water surface parameter set is established;
step 302, generating a second risk coefficient Txs of the flood from the second water surface parameter set, wherein the specific generation mode is as follows:
after carrying out dimensionless treatment on the soil saturation Bd, the water flow rate Ld and the silt accumulation speed Ys, the method comprises the following steps:
the significance of the parameters is:and->，/>The specific value of the weight coefficient can be adjusted and set by a user, and can also be obtained by mathematical analysis software through simulation analysis;
a second risk threshold value is preset, if the acquired second risk coefficient Txs is higher than the second risk threshold value, the current risk of flood generation is indicated, timely processing is needed, and at the moment, second alarm information is sent out;
in use, the contents of steps 301 and 302 are combined:
after being in continuous rainfall state in the monitoring area, if the rainwater is difficult to permeate into the water, only can accumulate in the relatively lower area, if the water can not be discharged in time, the flood risk is great, at this moment, the water flow rate Ld and the silt accumulation speed Ys are associated together, the influence degree of the flood risk is estimated from the angle of the water flow rate, comprehensive judgment is carried out on the flood risk in the monitoring area, an administrator in the monitoring area can select corresponding protection means according to the current water state change, and the flood influence is reduced through execution of monitoring.
Step four, if the first alarm information and the second alarm information are not received, generating a comprehensive risk coefficient based on the first risk coefficient Oxs and the second risk coefficient TxsAnd predicting by adopting a function fitting and secondary smooth index prediction method, and obtaining a predicted value ++of the weighted average>The method comprises the steps of carrying out a first treatment on the surface of the If the comprehensive risk coefficient->Predicted value of +.>If the comprehensive risk threshold is exceeded, a digital twin water conservancy model covering the monitoring area is established, and the digital twin water conservancy model is marked as a monitoring water conservancy digital twin model;
the fourth step comprises the following steps:
step 401, continuously acquiring a plurality of first risk coefficients Oxs and second risk coefficients Txs when the first alarm information and the second alarm information are not received; for example: first risk coefficientUp to->The method comprises the steps of carrying out a first treatment on the surface of the Second risk factor->Up to->；
Generating a composite risk coefficient from the first risk coefficient Oxs and the second risk coefficient TxsThe specific mode is as follows:
wherein,and->By comprehensive risk factors->And (3) characterizing flood risks in the monitoring area, wherein the characterization mode is as follows:
wherein,for the weight, its specific value can be set by the user adjustment, +.>Is the expected mean value of the first risk factor Oxs, < >>N is a positive integer greater than 1, which is the expected mean of the second risk coefficient Txs;
In application, on the basis of the first risk coefficient Oxs and the second risk coefficient Txs, comprehensive risk coefficients are formedBy comprehensive risk factors->Judging flood risk in the monitoring area;
step 402, integrating a plurality of risk coefficientsArranged along a time axis, fitted functionally according to its trend, marked ++after K-S test>Prediction function, by->Prediction function versus comprehensive risk factor>Predicting to generate a predicted value as a first prediction coefficient +.>；
According to a secondary smooth index prediction method, the comprehensive risk coefficientForming a prediction, generating a second prediction coefficient +.>；
The comprehensive risk coefficient is generated as followsRisk prediction value ++>；
Wherein,are all weight coefficients +.>The specific value of which can be set by the user;
when in use, the risk prediction value is obtained after weighting by two different prediction modesWith risk prediction valueAs a risk factor for the combination>When the flood risk does not exist in the monitoring area currently, predicting whether the flood risk possibly exists next, discovering the flood risk in advance, and processing in advance;
step 403, after the comprehensive risk threshold is preset, if the comprehensive risk coefficient Risk prediction value ++>When the comprehensive risk threshold is exceeded, at the moment, an electronic map which at least covers a monitoring area is obtained, and the topography characteristics of the monitoring area and flood discharge measures such as the existing flood discharge river channel, the existing flood discharge sewer and the like are marked on the electronic map;
using the marked electronic map and environmental condition parameters in the monitoring area, such as soil saturation, groundwater level depth, rainfall and the like; the current flood coverage area water surface parameters such as water level, flow velocity and flow, coverage area, flow direction and the like;
based on the Bp neural network model, combining the parameters, after training and testing, establishing a digital twin water conservancy model covering the monitoring area, and marking the digital twin water conservancy model as the monitoring water conservancy digital twin model.
In use, the contents of steps 401 to 403 are combined:
at present, no flood risk exists, and the comprehensive risk coefficient is obtainedAnd predicts it to obtain risk prediction value +.>The method comprises the steps of predicting whether the flood risk possibly exists in the monitoring area, if so, establishing a monitoring water conservancy digital twin model according to current condition parameters in the monitoring area, carrying out simulation analysis and prediction on the flood risk and the change of the flood risk in the monitoring area by the monitoring water conservancy digital twin model, and judging and monitoring the flood risk comprehensively in the monitoring area.
Fifthly, inputting rainfall and evaporation capacity as independent variables, performing simulation analysis on flood changes in a monitored area by using a monitoring water conservancy digital twin model, and if flood characteristics in the monitored area are obtained through prediction, matching corresponding flood drainage strategies from a pre-established flood drainage strategy library, and outputting the flood drainage strategies or outputting the flood drainage strategies after correction;
the fifth step comprises the following steps:
step 501, obtaining weather forecast information of the next stage, and at least obtaining rainfall and evaporation of water in a monitoring area; setting a prediction period, for example, one day is a prediction period, taking rainfall and evaporation as input independent variables, and carrying out simulation analysis on flood variation in a monitoring area by using a monitoring water conservancy digital twin model, wherein after at least one prediction period is obtained, the coverage area, the average depth and the water flow of the water body in the monitoring area are obtained; therefore, by means of the established monitoring water conservancy digital twin model, the effect of early warning on flood risks in the monitoring area is achieved;
step 502, collecting the existing drainage strategies through linear search on line or off line, building a drainage strategy library after summarizing, taking the coverage area and depth flow of the obtained water body as the flood characteristics, matching the corresponding drainage strategies from the drainage strategy library according to the correspondence between the flood characteristics and the drainage strategies, and outputting the drainage strategies;
Therefore, when the current impending flood risk is judged through prediction, the corresponding flood drainage strategy can be quickly matched, the time for making a scheme is saved, and the efficiency is improved;
step 503, at least taking the drainage strategy and the rainfall as input independent variables, performing simulation analysis by using a monitoring water conservancy digital twin model drainage strategy, judging whether the coverage area and the average depth of the water body in the monitoring area are reduced after the drainage strategy is executed, namely verifying whether the drainage strategy is effective, and outputting the drainage strategy if the drainage strategy is effective;
if the drainage strategy is invalid, various condition parameters of the drainage strategy, such as the flood discharge direction, the positions and the number of newly opened flood discharge channels and the like, are adjusted until the drainage strategy is valid, and the corrected drainage strategy is output.
In use, the contents of steps 501 to 503 are combined:
the rainfall and the evaporation capacity are obtained by predicting the following weather conditions, after a monitoring water conservancy digital twin model is established, whether the flood risk is generated in the monitoring area is judged, and after the monitoring effect is achieved, the prediction effect on the flood risk in the monitoring area can be achieved, so that if the rainfall still exists in the monitoring area, the risk of the monitoring area can be reduced, and the potential safety hazard brought by the monitoring area is reduced;
As a further improvement, after flood risk is predicted by monitoring the water conservancy digital twin model, flood characteristics and a pre-built flood drainage strategy library are obtained, so that after the flood risk exists, the corresponding flood drainage strategy can be quickly matched, and the feasibility of the flood drainage strategy is verified and corrected by combining simulation analysis; therefore, when the flood risk is possibly generated, the corresponding flood drainage strategy can be obtained quickly, the efficiency of formulating the flood drainage strategy is improved, and accordingly, when the flood risk is generated, the flood risk can be processed quickly, and the generation of larger potential safety hazards is avoided.
Referring to fig. 2, the present invention provides a digital twin-based water conservancy monitoring method and system, comprising:
the monitoring unit is used for determining the area where the water conservancy site is located as a monitoring area if the monitoring area is in a continuous rainfall state, setting monitoring points in the monitoring area, monitoring rainfall conditions in the monitoring area, establishing a rainfall condition set according to a monitoring result, generating a rainfall condition coefficient Jsx according to the rainfall condition set, and sending first early warning information to the outside if the rainfall condition coefficient Jsx is larger than a condition threshold;
the first evaluation unit selects a first sampling area in the monitoring area after receiving the first early warning information, collects current flood related parameters in the first sampling area, establishes a first water surface parameter set after summarizing, generates a first risk coefficient Oxs from the first water surface parameter set, and sends out first alarm information if the first risk coefficient is higher than a first risk threshold;
The second evaluation unit selects a second sampling area in the monitoring area after receiving the first alarm information, sets a data acquisition point in the second sampling area, acquires current flood state parameters, gathers and establishes a second water surface parameter set, establishes a second risk coefficient Txs by the second water surface parameter set, and sends out second alarm information if the second risk coefficient Txs is higher than a second risk threshold;
the model building unit generates a comprehensive risk coefficient based on the first risk coefficient Oxs and the second risk coefficient Txs if the first alarm information and the second alarm information are not receivedAnd predicting by adopting a function fitting and secondary smooth index prediction method, and obtaining a predicted value ++of the weighted average>The method comprises the steps of carrying out a first treatment on the surface of the If the comprehensive risk coefficient->Predicted value of +.>If the comprehensive risk threshold is exceeded, a digital twin water conservancy model covering the monitoring area is established, and the digital twin water conservancy model is marked as a monitoring water conservancy digital twin model;
and the scheme matching unit takes rainfall and evaporation as independent variables for input, the monitoring water conservancy digital twin model carries out simulation analysis on the flood change in the monitoring area, and if the flood characteristics in the monitoring area are obtained through prediction, the corresponding flood drainage strategy is matched from a pre-established flood drainage strategy library and is output or is output after correction.
In the application, the formulas are all dimensionality-removed numerical calculation, the formulas are formulas which are obtained by acquiring a large amount of data and performing software simulation and are closer to the actual situation, and preset parameters in the formulas can be adjusted and set by a person skilled in the art according to the actual application scene.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application.
Claims (10)
1. The water conservancy monitoring method based on digital twinning is characterized by comprising the following steps of: comprising the steps of (a) a step of,
if the monitoring area is in a continuous rainfall state, determining the area where the water conservancy site is located as a monitoring area, setting monitoring points in the monitoring area, monitoring rainfall conditions in the monitoring area, establishing a rainfall condition set according to a monitoring result, generating a rainfall condition coefficient Jsx according to the rainfall condition set, and if the rainfall condition coefficient Jsx is larger than a condition threshold, sending first early warning information to the outside;
wherein, the rainfall condition coefficient Jsx is generated by the rainfall condition set, and the specific method is as follows: after dimensionless treatment is carried out on the accumulated rainfall Lv and the ground water level rising speed Dv, the method is according to the following formula:
wherein, the meaning of the parameter is: />And->The specific value of the weight coefficient can be set by user adjustment or obtained by mathematical analysis software through simulation analysis;
if the acquired rainfall condition coefficient Jsx is larger than a preset condition threshold value, sending early warning information to the outside;
After receiving the first early warning information, selecting a first sampling area in a monitoring area, collecting current flood related parameters in the first sampling area, establishing a first water surface parameter set after summarizing, generating a first risk coefficient Oxs by the first water surface parameter set, and sending out first alarm information if the first risk coefficient Oxs is higher than a first risk threshold;
after receiving the first alarm information, selecting a second sampling area in the monitoring area, setting a data acquisition point in the second sampling area, acquiring current flood state parameters, summarizing and establishing a second water surface parameter set, establishing a second risk coefficient Txs by the second water surface parameter set, and sending out second alarm information if the second risk coefficient Txs is higher than a second risk threshold;
if the first alarm information and the second alarm information are not received, generating a comprehensive risk coefficient based on the first risk coefficient Oxs and the second risk coefficient TxsAnd predicting by adopting a function fitting and secondary smooth index prediction method, and obtaining a predicted value ++of the weighted average>The method comprises the steps of carrying out a first treatment on the surface of the If the comprehensive risk coefficient->Predicted value of +.>If the comprehensive risk threshold is exceeded, a digital twin water conservancy model covering the monitoring area is established, and the digital twin water conservancy model is marked as a monitoring water conservancy digital twin model;
And taking rainfall and evaporation as independent variables for input, carrying out simulation analysis on flood change in a monitoring area by using a monitoring water conservancy digital twin model, and if flood characteristics in the monitoring area are obtained through prediction, matching corresponding flood drainage strategies from a pre-established flood drainage strategy library, and outputting or outputting the flood drainage strategies after correction.
2. The digital twinning-based water conservancy monitoring method as set forth in claim 1, wherein:
after determining the areas where a plurality of water conservancy stations are located, determining the areas as monitoring areas, establishing an electronic map at least covering the monitoring areas, and setting monitoring points in the adjacent areas with the water conservancy stations;
if the current rainfall state is in the monitoring area and the current daily average rainfall is larger than the contemporaneous historical average value, continuously monitoring the underground water level and the rainfall process at the monitoring point, at least respectively obtaining the current accumulated rainfall Lv, and if the underground water level changes, obtaining the underground water level rising speed and determining the rising speed as the underground water level rising speed Dv;
and after the accumulated rainfall Lv and the ground water level rising speed Dv are summarized, a rainfall condition set is established.
3. The digital twinning-based water conservancy monitoring method as set forth in claim 1, wherein:
After receiving the first early warning information, randomly selecting a plurality of first sampling areas in a monitoring area, and collecting data in the first sampling areas through collecting equipment, wherein the data to be collected comprises:
acquiring the ground water level depth along a fixed time interval, if the ground water level of the first sampling area is continuously changed, acquiring the average increasing speed of the ground water level, and acquiring the ground water level rising speed Sv after analysis; identifying the water area coverage area in the first sampling area, and if the water area coverage area is changed, analyzing and acquiring the average increasing speed of the water area coverage area to generate the water area increasing speed Mv;
and after the water level rising speed Sv of the ground and the area increasing speed Mv of the water area are summarized, a first water surface parameter set is established.
4. A digital twin based water conservancy monitoring method according to claim 3 and wherein:
the first risk coefficient Oxs of the flood is generated by the first water surface parameter set, and the specific generation mode is as follows:
dimensionless processing is carried out on the water level rise speed Sv and the area rise speed Mv, historical average values of the water level rise speed Sv and the area rise speed Mv are respectively obtained, and a first risk coefficient Oxs is generated according to the following formula:
wherein (1)>Is the historical mean value of the water level rising speed Sv, < >>Is the historical mean value of area acceleration Mv, +. >Is->Is a weight coefficient, and->And->P is any positive integer between 3 and 6;
and if the acquired first risk coefficient Oxs is higher than the first risk threshold, sending out first alarm information.
5. The digital twinning-based water conservancy monitoring method as set forth in claim 4, wherein:
after receiving the first alarm information, setting a second sampling area at a position adjacent to the first sampling area in the monitoring area, and collecting the current flood state in the second sampling area, wherein the method comprises the following specific steps:
setting a plurality of data acquisition points with certain intervals in a second sampling area, and detecting the current state of soil at the data acquisition points to obtain the soil saturation Bd of the current soil; if the water body at or near the data acquisition point is in a flowing state, acquiring the water body flow velocity Ld; randomly selecting a plurality of data acquisition points, detecting and acquiring the accumulation and silt quantity at the points, further acquiring the accumulation speed of silt, and generating the accumulation and silt speed Ys;
and (3) summarizing the soil saturation Bd, the water flow rate Ld and the silt accumulation speed Ys, and then establishing a second water surface parameter set.
6. The digital twinning-based water conservancy monitoring method as set forth in claim 5, wherein:
The second risk coefficient Txs of the flood is generated by the second water surface parameter set, and the specific generation mode is as follows:
after carrying out dimensionless treatment on the soil saturation Bd, the water flow rate Ld and the silt accumulation speed Ys, the method comprises the following steps:
the significance of the parameters is: />And->，/>The specific value of the weight coefficient can be set by user adjustment or obtained by mathematical analysis software through simulation analysis;
and if the acquired second risk coefficient Txs is higher than the second risk threshold, sending out second alarm information.
7. The digital twinning-based water conservancy monitoring method as set forth in claim 1, wherein:
when the first alarm information and the second alarm information are not received, a plurality of first risk coefficients Oxs and second risk coefficients Txs are continuously obtained, and a comprehensive risk coefficient is generated by the first risk coefficients Oxs and the second risk coefficients TxsThe specific mode is as follows:
wherein (1)>And (2) andby comprehensive risk factors->And (3) characterizing flood risks in the monitoring area, wherein the characterization mode is as follows:
wherein (1)>For the weight, its specific value can be set by the user adjustment, +.>Is the expected mean value of the first risk factor Oxs, < >>N is a positive integer greater than 1, which is the expected mean of the second risk factor Txs.
8. The digital twinning-based water conservancy monitoring method as set forth in claim 7, wherein:
combining a plurality of comprehensive risk coefficientsArranged along a time axis, fitted functionally according to its trend, marked ++after K-S test>Prediction function, by->Prediction function versus comprehensive risk factor>Predicting to generate a predicted value as a first prediction coefficient +.>The method comprises the steps of carrying out a first treatment on the surface of the According to the quadratic smoothness index prediction method, the comprehensive risk coefficient is +.>Forming a prediction, generating a second prediction coefficient +.>；
The comprehensive risk coefficient is generated as followsRisk prediction value ++>；
Wherein (1)>Are all weight coefficients +.>The specific value of which is set by the user;
if the risk coefficient is integratedRisk prediction value ++>Acquiring an electronic map which at least covers a monitoring area when the comprehensive risk threshold is exceeded, and marking the topographic features of the monitoring area and the existing flood discharge measures on the electronic map;
using the marked electronic map and environmental condition parameters in the monitored area, and the current water surface parameters of the flood covered area; based on the Bp neural network model, combining the parameters, after training and testing, establishing a digital twin water conservancy model covering the monitoring area, and marking the digital twin water conservancy model as the monitoring water conservancy digital twin model.
9. The digital twinning-based water conservancy monitoring method as set forth in claim 1, wherein:
at least acquiring rainfall and evaporation capacity of water in a monitoring area, setting a prediction period, taking the rainfall and the evaporation capacity as input independent variables, and performing simulation analysis on flood change in the monitoring area by using a monitoring water conservancy digital twin model, wherein after at least acquiring one prediction period, the coverage area, the average depth and the water flow of the water body in the monitoring area are obtained;
the method comprises the steps of collecting existing drainage strategies through linear retrieval on line or off line, building a drainage strategy library after summarizing, taking the coverage area and depth flow of the predicted water body as flood characteristics, matching corresponding drainage strategies from the drainage strategy library according to the correspondence between the flood characteristics and the drainage strategies, and outputting the drainage strategies;
at least taking a drainage strategy and rainfall as input independent variables, performing simulation analysis by using a monitoring water conservancy digital twin model drainage strategy, judging whether the water coverage area and the average depth in a monitoring area are reduced after the drainage strategy is executed, namely verifying whether the drainage strategy is effective, and outputting the drainage strategy if the drainage strategy is effective;
If the drainage strategy is invalid, various condition parameters of the drainage strategy, such as the flood discharge direction, the positions and the number of newly opened flood discharge channels and the like, are adjusted until the drainage strategy is valid, and the corrected drainage strategy is output.
10. Water conservancy monitoring system based on digit twin, its characterized in that: comprising the following steps:
the monitoring unit is used for determining the area where the water conservancy site is located as a monitoring area if the monitoring area is in a continuous rainfall state, setting monitoring points in the monitoring area, monitoring rainfall conditions in the monitoring area, establishing a rainfall condition set according to a monitoring result, generating a rainfall condition coefficient Jsx according to the rainfall condition set, and sending first early warning information to the outside if the rainfall condition coefficient Jsx is larger than a condition threshold;
the first evaluation unit selects a first sampling area in the monitoring area after receiving the first early warning information, collects current flood related parameters in the first sampling area, establishes a first water surface parameter set after summarizing, generates a first risk coefficient Oxs from the first water surface parameter set, and sends out first alarm information if the first risk coefficient is higher than a first risk threshold;
the second evaluation unit selects a second sampling area in the monitoring area after receiving the first alarm information, sets a data acquisition point in the second sampling area, acquires current flood state parameters, gathers and establishes a second water surface parameter set, establishes a second risk coefficient Txs by the second water surface parameter set, and sends out second alarm information if the second risk coefficient Txs is higher than a second risk threshold;
The model building unit generates a comprehensive risk coefficient based on the first risk coefficient Oxs and the second risk coefficient Txs if the first alarm information and the second alarm information are not receivedAnd predicting by adopting a function fitting and secondary smooth index prediction method, and obtaining a predicted value ++of the weighted average>The method comprises the steps of carrying out a first treatment on the surface of the If the comprehensive risk coefficient->Predicted value of +.>If the comprehensive risk threshold is exceeded, a digital twin water conservancy model covering the monitoring area is established, and the digital twin water conservancy model is marked as a monitoring water conservancy digital twin model;
and the scheme matching unit takes rainfall and evaporation as independent variables for input, the monitoring water conservancy digital twin model carries out simulation analysis on the flood change in the monitoring area, and if the flood characteristics in the monitoring area are obtained through prediction, the corresponding flood drainage strategy is matched from a pre-established flood drainage strategy library and is output or is output after correction.
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