Hydrological model integration method and electronic equipment

Abstract

The invention discloses a hydrological model integration method and electronic equipment. The method comprises the steps of determining a hydrological model set according to attributes of hydrological models; after the preprocessed hydrological data to be input are determined, parameter adjustment and training are carried out on the hydrological model set according to the hydrological data, a target hydrological model set is obtained, and the target hydrological model set comprises a plurality of target hydrological models; determining a connection relationship according to the target hydrological model set, wherein the connection relationship comprises a set connection sequence and a set connection mode between the target hydrological models; a connected target hydrological model chain is determined according to the connection relation, and in the target hydrological model chain, output data of one target hydrological model is hydrological data of the next target hydrological model; and evaluating and adjusting the target hydrological model chain to obtain an adjusted hydrological model chain. Through the method, the tightness of the relation between the models is enhanced, the calculation difficulty and the calculation amount are reduced, and the accuracy and the robustness of using the hydrological model to carry out prediction are improved.

Description

Technical Field

[0001] The present application relates to the field of hydrological model construction, and in particular to a hydrological model integration method and electronic equipment. Background Art

[0002] In hydrology, mathematical models are used to simulate hydrological processes, such as rainfall-runoff processes and groundwater flow, in order to carry out work such as water resources management, flood forecasting, and hydrological prediction.

[0003] Existing model integration methods such as model fusion require unified training and evaluation of multiple single models so that multiple single models can be accurately applied in real life.

[0004] However, due to the complexity and uncertainty of hydrological processes, multiple single models are often unable to meet the needs of all situations. Multiple hydrological models increase the difficulty of calculation, and there are differences in the prediction results of multiple models, which may lead to low prediction accuracy and robustness. Summary of the invention

[0005] The present application provides a hydrological model integration method and electronic device for enhancing the closeness of the connection between models, reducing the difficulty of calculation, and improving the accuracy and robustness of prediction using hydrological models.

[0006] In a first aspect, the present application provides a hydrological model integration method, the method comprising: determining a hydrological model set according to the attributes of the hydrological model; after determining the pre-processed hydrological data to be input, adjusting and training the hydrological model set according to the hydrological data to obtain a target hydrological model set, the target hydrological model set including multiple target hydrological models; determining a connection relationship according to the target hydrological model set, the connection relationship including a set connection order and a set connection method between the target hydrological models; determining a connected target hydrological model chain according to the connection relationship, in which the output data of one target hydrological model is the hydrological data of the next target hydrological model; evaluating and adjusting the target hydrological model chain to obtain an adjusted hydrological model chain.

[0007] In the above embodiment, by establishing a connected target hydrological model chain, multiple hydrological models can be combined to form a chain prediction, thereby improving the prediction ability of the hydrological process. By evaluating and adjusting the hydrological model chain, the closeness of the connection between the models is enhanced, the calculation difficulty is reduced, and the accuracy and robustness of the prediction using the hydrological model are improved.

[0008] In combination with some embodiments of the first aspect, in some embodiments, after determining the pre-processed hydrological data to be input, the hydrological model set is adjusted and trained according to the hydrological data to obtain the step of the target hydrological model set, specifically including: performing a cleaning operation on the hydrological data to obtain first processed data, and the cleaning operation includes deduplication, correction, and deletion of abnormal data; performing interpolation processing on the first processed data according to an algorithm to obtain second processed data, and the interpolation processing includes filling in the data values ​​at the missing positions determined according to the algorithm; and determining the second processed data as the pre-processed hydrological data.

[0009] In the above embodiment, by cleaning operations such as deduplication, correction and deletion of abnormal data, duplicate, erroneous and abnormal data can be eliminated, data quality can be improved, and model errors caused by abnormal data can be reduced. Through interpolation processing, the data values ​​of the missing positions are filled according to the algorithm, which can restore the integrity of the data, reduce the impact of missing values ​​on subsequent analysis and model training, and improve the accuracy and reliability of the data, providing a more reliable data basis for the subsequent training and analysis of the hydrological model.

[0010] In combination with some embodiments of the first aspect, in some embodiments, before the step of performing a cleaning operation on the hydrological data to obtain first processed data, it also includes: determining historical observation data as the hydrological data.

[0011] In the above embodiments, the historical observation data is usually monitored and accumulated over a long period of time, and can better reflect the characteristics and changing trends of the hydrological system. Determining the historical observation data as hydrological data for training and verification of the hydrological model can improve the model's ability to predict hydrological processes. The fitting and verification results of the model on the historical observation data can reflect the accuracy and adaptability of the model, thereby improving the application effect of the model.

[0012] In combination with some embodiments of the first aspect, in some embodiments, the step of evaluating and adjusting the target hydrological model chain to obtain an adjusted hydrological model chain specifically includes: simulating the target hydrological model to obtain a simulation result; comparing the simulation result with the actual observation result to obtain a comparison result, wherein the actual observation result is an actual observation result of the hydrology; detecting whether the comparison result is within a fault tolerance range, which is an allowable error range between the simulation result and the actual observation result; if not within the fault tolerance range, adjusting the hydrological model chain according to the comparison result to obtain an adjusted hydrological model chain, wherein the adjustment operation includes deleting, adding and adjusting parameters of the hydrological model in the hydrological model chain.

[0013] In the above embodiment, if it is not within the fault tolerance range, the hydrological model needs to be adjusted to correct the deficiencies of the model. The hydrological model chain is adjusted by comparing the results, and the hydrological model is deleted, added, and parameters are adjusted to further improve the prediction accuracy of the hydrological model. The adjusted hydrological model chain can better reflect the actual hydrological process, reduce errors and deviations, and thus improve the accuracy and reliability of the prediction results.

[0014] In combination with some embodiments of the first aspect, in some embodiments, after the step of detecting whether the comparison result is within the error tolerance range, it also includes: if the comparison result is within the error tolerance range, no adjustment operation is performed on the hydrological model chain.

[0015] In the above embodiment, if the comparison result is within the tolerance range, it indicates that the output of the model chain is consistent with the actual observation data. Therefore, without adjusting the model chain, it can be confirmed that the model has a certain accuracy and reliability under the current conditions.

[0016] In combination with some embodiments of the first aspect, in some embodiments, if it is not within the fault tolerance range, the hydrological model chain is adjusted according to the comparison result, and after the step of obtaining the adjusted hydrological model chain, it also includes: adjusting the attributes of the hydrological data, which include the format and accuracy of the data; determining the adjusted hydrological model chain according to the attributes.

[0017] In the above embodiments, the format and accuracy of the data have an important impact on the accuracy of the model. By adjusting the attributes of the data, the accuracy and precision of the input data of the model chain can be improved, thereby improving the accuracy of the prediction and simulation results of the model. This can enhance the reliability of the model chain and provide more accurate hydrological prediction and decision support.

[0018] In combination with some embodiments of the first aspect, in some embodiments, after the step of evaluating and adjusting the target hydrological model chain to obtain the adjusted hydrological model chain, it also includes: determining a special hydrological model in the adjusted hydrological model chain; associating the special hydrological model with a set alarm device; and triggering the set alarm device after detecting that a parameter in the special hydrological model is greater than a set threshold.

[0019] In the above embodiment, by associating the special hydrological model with the alarm device, possible risks and abnormal conditions can be detected before the parameters exceed the set threshold. This can provide early warning and take appropriate measures in time to mitigate potential risks and losses, and also help improve the accuracy and efficiency of monitoring and control, reduce human errors and delays, which is important for water resources management, flood prevention and control, etc.

[0020] In a second aspect, an embodiment of the present application provides an electronic device, the electronic device comprising: A hydrological model set determination module, used for determining the hydrological model set according to the attributes of the hydrological model; A target hydrological model set acquisition module is used to adjust and train the hydrological model set according to the pre-processed hydrological data to be input, and obtain the target hydrological model set, which includes multiple target hydrological models; A connection relationship determination module, used to determine a connection relationship according to the target hydrological model set, wherein the connection relationship includes a set connection sequence and a set connection mode between the target hydrological models; A target hydrological model chain determination module is used to determine a connected target hydrological model chain according to the connection relationship, in which the output data of one target hydrological model is the hydrological data of the next target hydrological model; The adjusted hydrological model chain obtaining module is used to evaluate and adjust the target hydrological model chain to obtain the adjusted hydrological model chain.

[0021] In a third aspect, an embodiment of the present application provides an electronic device, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the electronic device to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer program product comprising instructions, which, when executed on an electronic device, enables the electronic device to execute the method described in the first aspect and any possible implementation of the first aspect.

[0023] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions. When the instructions are executed on an electronic device, the electronic device executes the method described in the first aspect and any possible implementation method of the first aspect.

[0024] It is understandable that the electronic devices provided in the second and third aspects, the computer program products provided in the fourth aspect, and the computer storage medium provided in the fifth aspect are all used to execute the methods provided in the embodiments of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding methods, which will not be repeated here.

[0025] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Since the electronic device determines the hydrological model set according to the attributes of the hydrological model, after determining the pre-processed hydrological data to be input, the hydrological model set is adjusted and trained according to the hydrological data to obtain the target hydrological model set and determine the connection relationship, and then the connected target hydrological model chain is determined, and then the target hydrological model chain is evaluated and adjusted to obtain the adjusted hydrological model chain. Therefore, the electronic device can obtain a hydrological model chain with strong correlation, which effectively solves the problem of weak correlation and large amount of calculation between hydrological models in the prior art, thereby enhancing the closeness of the connection between models, reducing the difficulty and amount of calculation, and improving the accuracy and robustness of prediction using hydrological models.

[0026] 2. Since the electronic device simulates the target hydrological model and obtains the simulation results, it compares them with the actual observation results to obtain the comparison results, and detects whether the comparison results are within the fault tolerance range. If not, the hydrological model chain is adjusted according to the comparison results to obtain the adjusted hydrological model chain, including deleting, adding and adjusting parameters of the hydrological models in the hydrological model chain. Therefore, the results obtained through the hydrological model chain are generally consistent with the actual data results, which effectively solves the problem of inaccurate prediction results of the hydrological model in the prior art, and can well reflect the actual hydrological process, reduce errors and deviations, and thus improve the accuracy and reliability of the prediction results.

[0027] 3. Since the electronic device performs a cleaning operation on the hydrological data to obtain the first processed data, the cleaning operation includes deduplication, correction, and deletion of abnormal data, and then interpolation processing is performed on the first processed data according to the algorithm to determine the pre-processed hydrological data. Therefore, the electronic device can obtain a more accurate hydrological model prediction result through multiple processing of the data, thereby eliminating duplicate, erroneous and abnormal data, improving data quality, reducing model errors caused by abnormal data, and providing a more reliable data basis for subsequent training and analysis of hydrological models. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a flow chart of a hydrological model integration method in an embodiment of the present application; Figure 2 It is a structural schematic diagram of the connection method of the hydrological model in the embodiment of the present application; Figure 3 is another flow chart of a hydrological model integration method in an embodiment of the present application; Figure 4 This is a schematic diagram of the functional module structure of the electronic device in the embodiment of the present application; Figure 5 It is a schematic diagram of the physical device structure of the electronic device in the embodiment of the present application. DETAILED DESCRIPTION

[0029] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more listed items.

[0030] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0031] For ease of understanding, the application scenarios of the embodiments of the present application are introduced below.

[0032] A certain area suffered from floods, and the relevant departments needed to use different hydrological models to predict flood-related data. Among them, the precipitation prediction model is used to predict the rainfall in the future, the water level prediction model is used to predict the changes in river water levels, and the water flow prediction model is used to predict the flow of rivers. When using these models, the data needs to be input into the model one by one for prediction. First, technicians use the precipitation prediction model to obtain the prediction results about rainfall. This model may be based on methods such as meteorological data, meteorological simulation, and statistical analysis to predict future rainfall. The prediction results include information such as the temporal distribution and spatial distribution of rainfall. Next, the precipitation prediction results are input into the water level prediction model. The water level prediction model usually simulates the rainfall runoff and flow transmission process based on parameters such as hydrological principles, topography, and river characteristics. The model can predict the changes in river water levels in the future based on the rainfall prediction results and real-time observation data. If the relevant departments also need to obtain the prediction results of water flow, they need to use other separate models to obtain the input data of the water flow prediction model. This may involve parameters such as basin area, soil type, and river channel geometry. These parameters can be determined through methods such as hydrological analysis, geographic information systems and topographic surveys. Once the input data for the water flow prediction model is obtained, water flow prediction can be carried out. This model usually combines rainfall forecast results with real-time observation data to predict the changes in river flow over a period of time in the future.

[0033] However, when the flood situation suddenly worsens, the above process may need to be repeated. The relevant departments need to adjust the input data of the rainfall prediction model and re-predict rainfall, water level and water flow based on real-time observation data and the actual flood situation.

[0034] It can be seen that in the above process, the connection between the models is not close enough, the calculation difficulty is high, and there are differences in the prediction results of multiple models, which may lead to low prediction accuracy and robustness.

[0035] By adopting the hydrological model integration method in the embodiment of the present application, a stable association between multiple hydrological models is achieved by constructing a hydrological model chain, which not only reduces the difficulty of calculation but also improves the robustness of the hydrological model and the accuracy of the results.

[0036] The following is a continuation of the previous scenario to introduce an application scenario of the method in the embodiment of the present application.

[0037] Continuing from the previous scenario, the relevant departments combined the precipitation prediction model, the water flow prediction model and the water level prediction model to form a hydrological model chain. The design of this model chain forms an organic connection between the models to ensure the continuity of data transmission and processing. Among them, the output data of the precipitation prediction model is the input data of the water flow prediction model, and the output data of the water flow prediction model is the input data of the water level prediction model. If relevant personnel want to know the corresponding water level prediction result when the precipitation is a certain data value, they can directly use the hydrological model chain. When the precipitation changes, the corresponding water level prediction result will also change accordingly.

[0038] If relevant personnel want to know the corresponding water level forecast result when the precipitation is a certain value, they can directly use this hydrological model chain. When the precipitation changes, the water level forecast results will also change, reflecting the evolution of the flood situation over time. The use of this joint model makes it easier for relevant personnel to obtain flood forecast results, understand the evolution trend of floods in a timely manner, and take countermeasures. This close connection and robust design enables the hydrological model chain to adapt to changes in the situation and provide more accurate and reliable forecast results.

[0039] For ease of understanding, the following describes the process of the method provided by this implementation in combination with the above scenario. Figure 1 , Figure 1 It is a flow chart of a hydrological model integration method in an embodiment of the present application.

[0040] S101, determining a hydrological model set according to the attributes of the hydrological model; Among them, the attributes of the hydrological model may include the application scenarios and output data of the hydrological model. For example, if the attributes are rainfall observation data, water level observation data, terrain data, etc., the rainfall observation hydrological model, water level observation hydrological model, and terrain observation hydrological model can be determined accordingly. Different target requirements may require different hydrological models. Relevant departments determine the required hydrological models based on specific application scenarios and target requirements. Based on different hydrological models, multiple models can be combined through model integration methods to determine the hydrological model set.

[0041] S102, after determining the pre-processed hydrological data to be input, adjusting parameters and training the hydrological model set according to the hydrological data to obtain a target hydrological model set, the target hydrological model set including a plurality of target hydrological models; Among them, hydrological data can be historical observation data, which is usually monitored and accumulated over a long period of time and can better reflect the characteristics and changing trends of the hydrological system. Determining historical observation data as hydrological data for the training and verification of hydrological models can improve the model's ability to predict hydrological processes.

[0042] Among them, parameter adjustment refers to optimizing and adjusting the parameters of the hydrological model according to the hydrological data to be input, so that the model can fit the actual hydrological process more accurately. The goal of parameter adjustment is to find the best combination of parameters so that the prediction results of the model are as close as possible to the observed data; training refers to using the existing hydrological data set to train and learn the model through the model optimization algorithm. The goal of training is to enable the model to learn the patterns and laws in the data by minimizing the prediction error or loss function, thereby improving the prediction ability of unknown data.

[0043] Specifically, after determining the hydrological data, the electronic device performs a cleaning operation on the hydrological data to obtain first processed data. The cleaning operation includes deduplication, correction, and deletion of abnormal data. More specifically, it checks whether there are duplicate data records in the hydrological data, that is, checks whether the same data appears multiple times in the data set, deletes the duplicate data records, and retains unique data; in addition, it corrects possible erroneous or inaccurate data in the hydrological data, with an emphasis on identifying and correcting obvious errors, such as data that exceeds a reasonable range or is inconsistent with other related data. The correction method can be determined according to the specific problem, which can be manual modification or automatic correction using data quality control methods; by setting some predefined data quality rules or based on statistical methods, it detects and deletes abnormal data in the hydrological data, wherein the abnormal data may be caused by sensor failure, environmental interference, etc., and its value is obviously abnormal or extremely inconsistent with other data.

[0044] After the electronic device determines the first processed data, it interpolates the first processed data according to an algorithm to obtain second processed data. The interpolation includes filling in the data values ​​at the missing positions determined by the algorithm. After the electronic device determines the second processed data, it determines the second processed data as the pre-processed hydrological data.

[0045] In some embodiments, multiple algorithms can be used to determine the optimal combination of parameters in the hydrological model and adjust the weight of the hydrological model. Through repeated iterations and optimization, the final target hydrological model set can better meet the needs of prediction and simulation.

[0046] S103, determining a connection relationship according to the target hydrological model set, where the connection relationship includes a connection sequence and a connection method set between the target hydrological models; Determining the connection relationship based on the target hydrological model set means that when using multiple hydrological models for integrated prediction, it is necessary to determine the connection order and connection method between models. The connection order refers to the execution order of multiple hydrological models when making predictions. Different hydrological models may have different inputs and outputs, so they need to be connected in a reasonable order. For example, a hydrological model may require the output of other models as input, so these models need to be connected in the correct order to ensure that each model can obtain the necessary input data.

[0047] The connection method refers to the data transmission and calculation method between multiple hydrological models. It can be serial connection or parallel connection, which is not limited here. Serial connection means that the output of one model is used as the input of the next model, and the data is transmitted in sequence to form a pipeline connection. Parallel connection means that the output of multiple models is combined or integrated to obtain the final prediction result. For example, the results of multiple models can be combined through weighted average, voting, decision tree, etc. to form the final integrated prediction result.

[0048] In practical applications, when determining the connection method, it is necessary to select appropriate data transmission and integration methods to obtain accurate and reliable integrated prediction results.

[0049] S104, determining a connected target hydrological model chain according to the connection relationship, in which the output data of one target hydrological model is the hydrological data of the next target hydrological model; After determining the connection relationship, the electronic device determines the target hydrological model chain after the connection according to the connection relationship. The target hydrological model chain is to connect these models in sequence according to the connection relationship to form a chain structure after determining the connection method and order of multiple hydrological models. In the target hydrological model chain, the output data of one model will be used as the hydrological data input of the next model. This means that the output data of each model will be directly passed to the next model as input, rather than being passed or integrated through other means.

[0050] S105. Evaluate and adjust the target hydrological model chain to obtain an adjusted hydrological model chain.

[0051] Use the target hydrological model chain to simulate the collected data. Model evaluation usually involves comparing the model output results with the observed data, analyzing the results of the model evaluation, and identifying the problems and sources of uncertainty in the hydrological model in the target hydrological model chain. For example, the hydrological model may not be able to adapt to certain specific hydrological events, or some parameters may have large uncertainties. In this case, adjustments to the target hydrological model chain are made based on the evaluation results and identified problems. Among them, adjustments specifically include modifying hydrological model parameters, introducing new hydrological models, and adjusting the hydrological model structure.

[0052] In the above embodiment, by establishing a connected target hydrological model chain, multiple hydrological models can be combined to form a chain prediction, thereby improving the prediction ability of the hydrological process. By evaluating and adjusting the hydrological model chain, the closeness of the connection between the models is enhanced, the calculation difficulty is reduced, and the accuracy and robustness of the prediction using the hydrological model are improved.

[0053] The following is a detailed description of the connections in the hydrological model chain. Figure 2 , Figure 2 It is a structural diagram of the connection method of the hydrological model in the embodiment of the present application.

[0054] Assume that we have three hydrological models A, B and C. Figure 2 In the example, when model A completes the calculation and generates output data, the output data will be directly passed to model B as the input of model B. After receiving the output data of model A, model B will use these data as its own input for calculation and generate its own output data. Similarly, the output data of model B will be directly passed to model C as the input of model C. Through this connection method, the target hydrological model chain forms an orderly data processing flow, and each model receives the output data of the previous model as input in turn, and generates its own output data to pass to the next model. In this way, the entire target hydrological model chain can complete continuous data processing and prediction tasks.

[0055] It should be noted that Figure 2 This is only a structural diagram of the open-loop situation of the hydrological model chain. In practical applications, the hydrological model chain can be a closed loop, which is not limited here.

[0056] In some embodiments, the adjustment of the hydrological model is not very precise, because overly precise adjustment will not only increase the amount of calculation but also lead to lower efficiency of the model. In addition, an alarm device can be set on a special hydrological model. If some special circumstances occur, such as a tsunami or flood, the alarm device can be directly triggered so that relevant staff can handle it in time.

[0057] The following is a supplement to the process of this embodiment. Figure 3 , Figure 3 It is another flow chart of a hydrological model integration method in an embodiment of the present application.

[0058] S301, simulating the target hydrological model to obtain simulation results; Collect the required input data, such as rainfall data, evapotranspiration data, soil moisture data, etc. These data can come from measured data or the output of other models. According to the requirements of the hydrological model, configure the required parameters, input the configured model and prepared data into the model for simulation. The hydrological model will calculate based on the input data and parameters, simulate the changes in the hydrological process, and then obtain simulation results such as changes in flow and groundwater level.

[0059] S302, comparing the simulation result with the actual observation result to obtain a comparison result, where the actual observation result is an actual observation result of hydrology; The simulation results and the actual observation results are compared by using appropriate comparison methods. Based on the comparison methods and statistical indicators, the change trends, absolute value differences, correlations, etc. of the simulation results and the actual observation results are compared.

[0060] To obtain the comparison results. The actual observation results refer to the data obtained by observing the hydrological process in practice. Before making a comparison, it is necessary to ensure that the actual observation results have been obtained. The actual observation can be obtained by collecting data through monitoring equipment such as meteorological stations, hydrological stations, radars, etc., or through manual observation and other means.

[0061] S303, detecting whether the comparison result is within a tolerance range, where the tolerance range is a permissible error range between the simulation result and the actual observation result; After obtaining the comparison result, the electronic equipment performs an error analysis on the comparison result to detect whether the comparison result is within the fault tolerance range. The fault tolerance range refers to the error range allowed between the simulation result and the actual observation result. The fault tolerance range can be set according to specific requirements and actual conditions, and is usually based on statistical methods and hydrological knowledge. For example, it is estimated based on the discreteness and uncertainty of the observation data.

[0062] If the comparison result is not within the error tolerance range, step S304 is executed; If the comparison result is within the error tolerance range, step S308 is executed.

[0063] S304, adjusting the hydrological model chain according to the comparison result to obtain an adjusted hydrological model chain, wherein the adjustment operation includes deleting, adding, and adjusting parameters of the hydrological models in the hydrological model chain; If the comparison result is not within the tolerance range, the accuracy and reliability of the simulation results can be improved by analyzing the causes of the errors, finding measures such as improving model parameters and improving observation equipment. Specifically, determine whether the model needs to be deleted based on the error sources analyzed in the comparison results. If a hydrological model performs poorly and has large errors during the comparison process, consider deleting it from the hydrological model chain. The basis for deletion can be the error calculation indicators of the comparison results, such as absolute error, relative error, etc.; determine whether a new hydrological model needs to be added based on the error sources analyzed in the comparison results. If the comparison results show that the simulation results lack certain features or cannot explain part of the observation results, consider adding a new hydrological model. The basis for adding can be the characteristics of the observation data, hydrological knowledge, and the needs of the simulation results; in addition, the parameters in the hydrological model can be adjusted. The purpose of the adjustment is to make the model better fit the actual observation results to ensure the accuracy and reliability of the parameters in the hydrological model. In addition, the electronic device can also adjust the properties of the hydrological data, which include the format and accuracy of the data; determine the adjusted hydrological model chain based on the properties. Since the format and accuracy of the data have an important impact on the accuracy of the model, by adjusting the properties of the data, the accuracy and precision of the input data of the model chain can be improved, thereby improving the accuracy of the prediction and simulation results of the hydrological model.

[0064] According to the results of deletion, addition and parameter adjustment, the adjusted hydrological model chain is determined. In some embodiments, the hydrological model in the adjusted hydrological model chain can be verified again to evaluate the adjustment effect and determine whether the adjusted model chain can better fit the actual observation results. If the comparison result still does not meet the requirements, it may be necessary to further adjust the hydrological model chain or re-optimize the parameters.

[0065] S305, determining a special hydrological model in the adjusted hydrological model chain; Special hydrological models can be models with special processing mechanisms (such as groundwater models, flood storage and detention models, etc.), models used for special purposes (such as reservoir operation models, sediment transport models, etc.), or models used for special types of basins (such as cold region basin models, tropical rainforest basin models, etc.). Special hydrological models are determined in this adjusted hydrological model chain.

[0066] S306, associating the special hydrological model with a set alarm device; After determining the special hydrological model, the electronic device associates the special hydrological model with the set alarm device.

[0067] S307: After detecting that the parameter in the special hydrological model is greater than the set threshold, the set alarm device is triggered.

[0068] After associating the special hydrological model with the set alarm device, the electronic device detects whether the parameter in the special hydrological model is greater than the set threshold. If it is greater than the set threshold, the set alarm device is triggered. Specifically, the trigger condition may be a specific threshold such as water level, flow, rainfall, etc. For example, in a flood warning system, the trigger condition may be exceeding a certain warning water level or rainfall, etc. According to the determined trigger conditions, the parameters and settings of the alarm device are configured. The alarm device may be an audible and visual alarm, an automatic SMS sending system, a remote control device, etc. A suitable alarm device may be selected based on actual needs and feasibility considerations.

[0069] The simulation results of the special hydrological model are data-connected to the alarm device, so that the output results of the special hydrological model are connected to the input or control signal of the alarm device. In this way, during the simulation process, when the output of the special hydrological model reaches the trigger condition, a signal can be automatically sent to the alarm device. Specifically, the alarm device can also be tested after connection to ensure that the linkage between the special hydrological model and the alarm device works normally. The response time, accuracy and stability of the alarm device can be tested by setting different simulation scenarios and trigger conditions. In addition, after confirming that the linkage between the special hydrological model and the alarm device is reliable, it is applied to the actual hydrological monitoring and early warning system, and the alarm device and the special hydrological model are regularly maintained and updated to ensure the reliability and flexibility of the entire system.

[0070] S308: Do not adjust the hydrological model chain.

[0071] If the comparison result is within the tolerance range, it is considered that the comparison result is acceptable, the simulation result has a certain consistency and accuracy with the actual observation result, and the electronic equipment does not adjust the hydrological model chain.

[0072] In the above embodiment, the prediction accuracy of the hydrological model can be further improved by adjusting the hydrological model, correcting the deficiencies of the model, deleting, adding and adjusting parameters of the hydrological model. The adjusted hydrological model chain can better reflect the actual hydrological process and reduce errors and deviations. In addition, by associating a special hydrological model with an alarm device, possible risks and abnormal conditions can be detected before the parameters exceed the set threshold. This can provide early warning and take appropriate measures in time to reduce potential risks and losses. It also helps to improve the accuracy and efficiency of monitoring and control and reduce human errors and delays, which plays an important role in water resources management, flood prevention and control, etc.

[0073] The following describes an electronic device in an embodiment of the present application from the perspective of a module. Figure 4 , Figure 4 It is a schematic diagram of the functional module structure of the electronic device in the embodiment of the present application.

[0074] A hydrological model set determination module 401 is used to determine a hydrological model set according to the attributes of the hydrological model; The target hydrological model set acquisition module 402 is used to adjust and train the hydrological model set according to the pre-processed hydrological data to be input, and obtain the target hydrological model set, which includes multiple target hydrological models; A connection relationship determination module 403 is used to determine a connection relationship according to the target hydrological model set, wherein the connection relationship includes a connection sequence and a connection mode set between the target hydrological models; A target hydrological model chain determining module 404 is used to determine a connected target hydrological model chain according to the connection relationship, in which the output data of one target hydrological model is the hydrological data of the next target hydrological model; The adjusted hydrological model chain obtaining module 405 is used to evaluate and adjust the target hydrological model chain to obtain an adjusted hydrological model chain.

[0075] In some embodiments, the target hydrological model set acquisition module specifically includes: Performing a cleaning operation on the hydrological data to obtain first processed data, wherein the cleaning operation includes deduplication, correction, and deletion of abnormal data; Performing interpolation processing on the first processed data according to an algorithm to obtain second processed data, wherein the interpolation processing includes filling in data values ​​at missing positions determined according to the algorithm; The second processed data is determined as the pre-processed hydrological data.

[0076] In some embodiments, the target hydrological model set acquisition module further includes: The historical observation data are determined as the hydrological data.

[0077] In some embodiments, the adjusted hydrological model chain obtaining module specifically includes: The target hydrological model is simulated to obtain simulation results; Comparing the simulation result with the actual observation result to obtain a comparison result, wherein the actual observation result is an actual hydrological observation result; Check whether the comparison result is within the error tolerance range, which is the error range allowed between the simulation result and the actual observation result; If it is not within the fault tolerance range, the hydrological model chain is adjusted according to the comparison result to obtain an adjusted hydrological model chain. The adjustment operation includes deleting, adding and adjusting parameters of the hydrological models in the hydrological model chain.

[0078] In some embodiments, the adjusted hydrological model chain obtaining module further includes: If the comparison result is within the tolerance range, no adjustment operation will be performed on the hydrological model chain.

[0079] In some embodiments, the adjusted hydrological model chain obtaining module further includes: Adjust the attributes of the hydrological data, including the format and accuracy of the data; The adjusted hydrological model chain is determined according to the attribute.

[0080] In some embodiments, the adjusted hydrological model chain obtaining module further includes: determining a specific hydrological model in the adjusted hydrological model chain; Associating the special hydrological model with a set alarm device; After detecting that the parameter in the special hydrological model is greater than the set threshold, the set alarm device is triggered.

[0081] The above describes an electronic device in the embodiment of the present application from the perspective of modular functional entities. The following describes an electronic device in the embodiment of the present application from the perspective of hardware processing. Figure 5 , Figure 5 It is a schematic diagram of the physical device structure of the electronic device in the embodiment of the present application.

[0082] The user terminal 500 includes: one or more processors 501 ( Figure 5 Taking a processor 501 as an example), a memory 502, an input device 503 and an output device 504. In some embodiments of the present invention, the processor 501, the memory 502, the input device 503 and the output device 504 may be connected via a bus or other means, wherein: Figure 5The example of connecting through bus is taken in the following.

[0083] The processor 501 calls the computer instruction so that the computer program is executed by the processor to implement a hydrological model integration method in an embodiment of the present application.

[0084] The memory 502 is used to store computer program codes, where the computer program codes include computer instructions.

[0085] The input device 503 is used to input hydrological data.

[0086] The output device 504 is used to trigger an alarm device.

[0087] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0088] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0089] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) mode. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk), etc.

[0090] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A hydrological model integration method, characterized in that: The method comprises: Determining a hydrological model set according to the attributes of the hydrological model; After determining the pre-processed hydrological data to be input, adjusting parameters and training the hydrological model set according to the hydrological data to obtain a target hydrological model set, wherein the target hydrological model set includes a plurality of target hydrological models; Determine a connection relationship according to the target hydrological model set, wherein the connection relationship includes a set connection sequence and a set connection mode between the target hydrological models; Determine a connected target hydrological model chain according to the connection relationship, in which the output data of one target hydrological model is the hydrological data of the next target hydrological model; The target hydrological model chain is evaluated and adjusted to obtain an adjusted hydrological model chain.

2. The method according to claim 1, characterized in that After determining the pre-processed hydrological data to be input, the step of adjusting and training the hydrological model set according to the hydrological data to obtain the target hydrological model set specifically includes: Performing a cleaning operation on the hydrological data to obtain first processed data, wherein the cleaning operation includes deduplication, correction, and deletion of abnormal data; Performing interpolation processing on the first processed data according to an algorithm to obtain second processed data, wherein the interpolation processing includes filling in data values ​​at missing positions determined according to the algorithm; The second processed data is determined as the pre-processed hydrological data.

3. The method according to claim 2, characterized in that Before the step of performing a cleaning operation on the hydrological data to obtain first processed data, the method further includes: The historical observation data are determined as the hydrological data.

4. The method according to claim 1, characterized in that The step of evaluating and adjusting the target hydrological model chain to obtain an adjusted hydrological model chain specifically includes: Simulating the target hydrological model to obtain simulation results; Comparing the simulation result with the actual observation result to obtain a comparison result, wherein the actual observation result is an actual observation result of hydrology; Detecting whether the comparison result is within a tolerance range, where the tolerance range is the allowable error range between the simulation result and the actual observation result; If it is not within the fault tolerance range, the hydrological model chain is adjusted according to the comparison result to obtain an adjusted hydrological model chain, wherein the adjustment operation includes deleting, adding and adjusting parameters of the hydrological models in the hydrological model chain.

5. The method according to claim 4, characterized in that After the step of detecting whether the comparison result is within the error tolerance range, the method further includes: If the comparison result is within the error tolerance range, no adjustment operation is performed on the hydrological model chain.

6. The method according to claim 4, characterized in that After the step of adjusting the hydrological model chain according to the comparison result to obtain an adjusted hydrological model chain if the hydrological model chain is not within the fault tolerance range, the method further includes: Adjusting the attributes of the hydrological data, wherein the attributes include the format and accuracy of the data; The adjusted hydrological model chain is determined according to the attributes.

7. The method according to claim 1, characterized in that After the step of evaluating and adjusting the target hydrological model chain to obtain an adjusted hydrological model chain, the method further includes: determining a specific hydrological model in the adjusted hydrological model chain; Associating the special hydrological model with a set alarm device; After detecting that the parameter in the special hydrological model is greater than a set threshold, the set alarm device is triggered.

8. An electronic device, characterized in that: include: A hydrological model set determination module, used for determining a hydrological model set according to the attributes of the hydrological model; A target hydrological model set acquisition module is used to adjust and train the hydrological model set according to the hydrological data to be input after determining the pre-processed hydrological data to be input, so as to obtain the target hydrological model set, wherein the target hydrological model set includes a plurality of target hydrological models; A connection relationship determination module, used to determine a connection relationship according to the target hydrological model set, wherein the connection relationship includes a set connection sequence and a set connection mode between the target hydrological models; A target hydrological model chain determination module, used to determine a connected target hydrological model chain according to the connection relationship, in which the output data of one target hydrological model is the hydrological data of the next target hydrological model; The adjusted hydrological model chain obtaining module is used to evaluate and adjust the target hydrological model chain to obtain the adjusted hydrological model chain.

9. An electronic device, characterized in that: include: One or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the electronic device to execute the method as described in any one of claims 1-7.

10. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on an electronic device, the electronic device is caused to execute the method as claimed in any one of claims 1 to 7.

Images