Hydrological situation analysis and early warning method and system based on low code configuration

Abstract

The invention discloses a hydrological situation analysis and early warning method based on low code configuration, and relates to the technical field of hydrological information processing and early warning decision, and the method comprises the steps: carrying out the standardization processing of basic parameters of a drainage basin, and generating a drainage basin feature vector; a preset hydrological model template library is adopted to match the adaptive model, an optimal hydrological calculation model is determined through similarity calculation according to parameter values in the drainage basin feature vectors, and a low-code configuration file is generated; inputting rainfall data and water level data obtained through real-time monitoring into a low-code configuration file, and calculating through an adaptive model to obtain a hydrological situation index; and when the hydrological situation index is greater than a preset grading early warning threshold value, triggering an early warning signal, and pushing early warning information to a specified terminal through a predefined early warning strategy. According to the method, a standardized drainage basin feature vector construction method and an automatic model matching mechanism are adopted, and the problems of high professional threshold and response lag in the hydrological model configuration and situation judgment process are solved.

Description

Technical Field

[0001] This invention relates to the field of hydrological information processing and early warning decision-making technology, and in particular to a hydrological situation analysis and early warning method and system based on low-code configuration. Background Technology

[0002] Traditional hydrological forecasting systems typically rely on specialized hydrological models (such as the SCS-CN model and the HEC-HMS model) for modeling and calculation. While these models offer high accuracy and scientific rigor, their complex configuration processes and high user skill requirements make them unsuitable for the rapid deployment and efficient response needs of grassroots water resources units and in emergency scenarios. In recent years, with the rise of technologies such as visual modeling, low-code development, and automatic model matching, hydrological forecasting and early warning systems based on simplified configuration processes have gradually become a research hotspot. Low-code platforms, with their "visual configuration + automatic generation" development philosophy, provide an efficient and flexible solution for hydrological model construction. However, most existing systems remain at the general platform level, lacking dynamic adaptation capabilities for watershed characteristic parameters, and the model calling process lacks an intelligent selection mechanism, making it difficult to maintain accuracy and adaptability under complex and ever-changing watershed conditions.

[0003] Some studies have attempted to combine data-driven machine learning methods with traditional hydrological models to improve the intelligence of model predictions. However, these methods often rely on large-scale sample training and long-term data accumulation, and their effectiveness drops significantly when data is insufficient or regional characteristics vary considerably. Meanwhile, most existing hydrological early warning systems lack unified configuration standards and modular interfaces, leading to difficulties in system migration and high maintenance costs. Regarding model adaptation, traditional methods typically rely on experts manually selecting model types, which is time-consuming and easily influenced by subjective judgment, lacking objectivity and universality. Furthermore, in terms of hydrological situation index construction and early warning triggering mechanisms, existing methods mostly use single parameters or static rules, making it difficult to comprehensively reflect the overall risk situation of the watershed and lacking the ability to flexibly adjust early warning strategies. Therefore, there is an urgent need for a low-code hydrological situation analysis system that can achieve automatic model matching, parameter standardization, and flexible configuration of early warning rules to achieve more efficient and universal hydrological forecasting and early warning capabilities.

[0004] In summary, existing hydrological situation analysis and early warning technologies suffer from problems such as complex model configuration, poor adaptability, low deployment efficiency, and rigid early warning mechanisms. This invention provides a low-code configuration-based hydrological situation analysis and early warning method and system. It employs a standardized watershed feature vector construction method and an automatic model matching mechanism, effectively improving the system's versatility and deployment efficiency, and solving the problems of high professional barriers and slow response in hydrological model configuration and situation assessment. Summary of the Invention

[0005] In view of the problems of existing hydrological models being complex to configure, having weak model adaptability, and having poor early warning mechanisms, this invention is proposed.

[0006] Therefore, the problem to be solved by this invention is how to achieve intelligent adaptation of hydrological models to different watershed characteristics through low-code visual configuration, and combine real-time monitoring data to calculate situation indexes and perform graded early warning, thereby constructing a hydrological situation analysis and early warning system that is flexible in configuration, efficient in deployment, and timely in response.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, embodiments of the present invention provide a hydrological situation analysis and early warning method based on low-code configuration, comprising, The system receives basic watershed parameters input by the user through a visual configuration interface, performs standardization processing on the basic watershed parameters, and generates a watershed feature vector V=[A',L',P']. The basic watershed parameters include watershed area A, river length L, and historical rainfall threshold P, where A', L', and P' are the standardized watershed area, river length, and rainfall threshold parameters, respectively. Based on the watershed feature vector V, a preset hydrological model template library is used to match and adapt the model M. The adapted model M determines the optimal hydrological calculation model based on the parameter values ​​of the watershed feature vector V through similarity calculation, and generates a low-code configuration file Config. The real-time monitoring data of rainfall R and water level H are input into the low-code configuration file Config, and the hydrological situation index WI is calculated through the adaptation model M. When the hydrological situation index WI is greater than the preset graded warning threshold, a warning signal is triggered, and warning information is pushed to the designated terminal through the warning strategy predefined in the low-code configuration file Config.

[0008] As a preferred embodiment of the hydrological situation analysis and early warning method based on low-code configuration described in this invention, wherein: when the hydrological situation index WI is greater than a preset graded early warning threshold, an early warning signal is triggered, and early warning information is pushed to a designated terminal through the early warning strategy predefined in the low-code configuration file Config, including: The hydrological situation index WI value and the preset graded early warning thresholds are judged, wherein the preset graded early warning thresholds include a first-level threshold T1, a second-level threshold T2 and a third-level threshold T3, and satisfy the condition that the first-level threshold T1 < the second-level threshold T2 < the third-level threshold T3. When the hydrological situation index WI value is less than the first-level threshold T1, a primary warning signal is triggered. The primary warning strategy associated with the first-level threshold T1 is extracted from the low-code configuration file Config. The primary warning strategy includes the warning information template MT1 and the first target terminal list LT1. Based on the structured fields of the warning information template MT1, the current watershed feature vector V=[A',L',P'], real-time rainfall data R, and water level data H are filled in to generate a standardized warning message PT1; Through the communication interface integrated in the low-code configuration file Config, the standardized early warning message PT1 is pushed to the mobile terminal of the flood control personnel in a specified data format according to the address information of the first target terminal list LT1; When the hydrological situation index WI value is greater than or equal to the first-level threshold T1 and less than the second-level threshold T1, the intermediate warning signal is triggered, and the strategy upgrade logic in the low-code configuration file Config is executed. When the hydrological situation index WI value is greater than or equal to the second-level threshold T1 and less than the third-level threshold T1, an emergency warning signal is triggered, and the cross-departmental linkage mechanism in the low-code configuration file Config is activated.

[0009] As a preferred embodiment of the low-code configuration-based hydrological situation analysis and early warning method of the present invention, the strategy upgrade logic includes: While retaining the execution link of the primary early warning strategy, the emergency response strategy associated with the second-level threshold T2 is activated, wherein the emergency response strategy includes the on-site handling instruction set IT2 and the second target terminal list LT2. The on-site handling instruction set IT2 and real-time hydrological data are bound together to generate an emergency task package ET2, which is then synchronously pushed to the emergency command platform in the second target terminal list LT2 through the government network channel.

[0010] As a preferred embodiment of the low-code configuration-based hydrological situation analysis and early warning method of the present invention, wherein: the method for obtaining the hydrological situation index WI is as follows: The real-time rainfall data R and water level data H of the watershed monitoring station are obtained through the data interface module in the low-code configuration file Config. The rainfall data R includes a timestamp TR and a rainfall intensity value IR; the water level data H includes a timestamp TH and a water level height value IH. The real-time rainfall data R and the water level data H are synchronized and verified over time. When the difference between the timestamp TR and the timestamp TH is greater than the preset time window ΔT, a data compensation algorithm is triggered to interpolate the data for the missing time period. The synchronously verified rainfall data R and water level data H are fused with the watershed feature vector V=[A',L',P'] to generate a comprehensive input matrix X. The calculation function f in the adaptation model M stored in the low-code configuration file Config is called, and the comprehensive input matrix X is used as the function parameter input. The calculation function f performs weighted calculation on the rainfall data R and the water level data H according to the parameter weight allocation strategy in the watershed feature vector V=[A',L',P']. The watershed runoff coefficient β and the confluence time τ are calculated using the hydrological response algorithm built into the adaptation model M. The watershed runoff coefficient β, the runoff time τ, and the standardized rainfall threshold parameter P' are coupled and calculated to generate the hydrological situation index WI through the calculation function f. The hydrological situation index WI is stored in the cache area of ​​the low-code configuration file Config, and a timestamp identifier TWI is generated at the same time; The validity of the hydrological situation index WI is verified through the status module of the low-code configuration file Config. When the hydrological situation index WI is greater than the preset reasonable range, a data anomaly marker is triggered and the recalculation process is started.

[0011] As a preferred embodiment of the hydrological situation analysis and early warning method based on low-code configuration described in this invention, the method for generating the low-code configuration file Config is as follows: All candidate hydrological calculation models are extracted from a pre-set hydrological model template library. Each candidate hydrological calculation model includes a standard watershed feature vector Vs=[As',Ls',Ps'] and a corresponding model parameter set Θs. The standard watershed feature vector Vs serves as the feature identifier for each candidate model. The similarity score Sim between the watershed feature vector V=[A',L',P'] and the standard watershed feature vector Vs=[As',Ls',Ps'] is calculated using the Euclidean distance algorithm. The similarity scores Sim of all candidate hydrological calculation models are sorted, and the candidate hydrological calculation model with the smallest similarity score Sim is selected as the fitting model M. At the same time, the model parameter set Θs and the calculation function f corresponding to the fitting model M are obtained. Based on the model structure of the adaptation model M, a basic framework for generating a low-code configuration file Config is generated, wherein the low-code configuration file Config includes a data interface module, a computing engine module, a status module, and an early warning management module. The calculation function f and the model parameter set Θs are embedded into the calculation engine module, and the weight allocation strategy of the standardized watershed area A', river length L' and rainfall threshold parameter P' of the watershed feature vector V=[A',L',P'] is configured. Based on the parameter characteristics of the watershed feature vector V, a first-level threshold T1, a second-level threshold T2, and a third-level threshold T3 are preset in the early warning management module. At the same time, an early warning information template MT1, a first target terminal list LT1, an on-site handling instruction set IT2, and a second target terminal list LT2 associated with each threshold are configured. The data interface module is pre-configured with communication protocols and data format standards for acquiring the rainfall data R and the water level data H, while the status module sets a reasonable range for the hydrological situation index WI.

[0012] As a preferred embodiment of the low-code configuration-based hydrological situation analysis and early warning method of the present invention, wherein: the method for obtaining the watershed feature vector is as follows: The system receives basic watershed parameters input by the user through a visual configuration interface, performs data type verification and numerical range verification on the basic watershed parameters, and triggers an error message and prompts the user to re-enter the parameters when the basic watershed parameters exceed a preset reasonable range. Extract the watershed parameter standardization benchmark library built into the system to obtain the maximum and minimum benchmark values ​​corresponding to the basic parameters of the watershed; The watershed basic parameters are standardized using the min-max standardization algorithm, and the standardized watershed basic parameters are calculated. The standardized watershed basic parameters are combined in a fixed order to generate the watershed feature vector V=[A',L',P'], which is then stored in the system cache area. The standardization processing result is displayed on the visualization configuration interface.

[0013] As a preferred embodiment of the hydrological situation analysis and early warning method based on low-code configuration described in this invention, the maximum and minimum benchmark values ​​corresponding to the basic parameters of the watershed include the maximum benchmark value Amax and the minimum benchmark value Amin corresponding to the watershed area A, the maximum benchmark value Lmax and the minimum benchmark value Lmin corresponding to the river length L, and the maximum benchmark value Pmax and the minimum benchmark value Pmin corresponding to the historical rainfall threshold P.

[0014] Secondly, embodiments of the present invention provide a hydrological situation analysis and early warning system based on low-code configuration, comprising: The feature vector generation module is used to receive the basic watershed parameters input by the user through a visual configuration interface, standardize the basic watershed parameters, and generate a watershed feature vector V=[A',L',P'], wherein the basic watershed parameters include watershed area A, river length L, and historical rainfall threshold P, and A', L', and P' are the standardized watershed area, river length, and rainfall threshold parameters, respectively. The hydrological model matching and configuration generation module, based on the watershed feature vector V, uses a preset hydrological model template library to match and adapt the model M. The adapted model M determines the optimal hydrological calculation model based on the parameter values ​​of the watershed feature vector V through similarity calculation, and generates a low-code configuration file Config. The hydrological situation calculation module inputs the real-time monitored rainfall data R and water level data H into the low-code configuration file Config, which is used to calculate the hydrological situation index WI through the adaptation model M. The early warning triggering and information push module is used to trigger an early warning signal when the hydrological situation index WI is greater than the preset graded early warning threshold, and push early warning information to the designated terminal through the early warning strategy predefined in the low-code configuration file Config.

[0015] Thirdly, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, they implement the steps of the hydrological situation analysis and early warning method based on low-code configuration as described in the first aspect of the present invention.

[0016] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, they implement the steps of the hydrological situation analysis and early warning method based on low-code configuration as described in the first aspect of the present invention.

[0017] Compared with existing technologies, the beneficial effects of this invention are as follows: Basic watershed parameters are obtained and standardized through a visual configuration interface to generate a watershed feature vector V=[A',L',P'], achieving data structure standardization and model input uniformity; the optimal hydrological model is matched using the Euclidean distance algorithm based on the watershed feature vector, generating a low-code configuration file Config, enabling rapid adaptation of the hydrological model and automatic construction of the computational framework, improving system deployment efficiency and customization capabilities; real-time rainfall and water level data are input into the adaptation model M to calculate the hydrological situation index WI, fusing multi-source data and considering watershed parameter weights, achieving accurate quantification of complex hydrological situations; when WI exceeds a preset grading threshold, different levels of early warning information are pushed through predefined strategies in the low-code configuration file, achieving tiered response, automatic linkage, and cross-departmental collaboration, effectively improving the accuracy of early warning and the efficiency of handling sudden hydrological events in the watershed. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a flowchart of a low-code configuration-based hydrological situation analysis and early warning method. Detailed Implementation

[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0020] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0021] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0022] As mentioned in the background section, some research has attempted to combine data-driven machine learning methods with traditional hydrological models to improve the intelligence of model predictions. However, such methods often rely on large-scale sample training and long-term data accumulation, and their effectiveness drops significantly when data is insufficient or regional characteristics differ greatly. Meanwhile, most existing hydrological early warning systems lack unified configuration standards and modular interfaces, leading to difficulties in system migration and high maintenance costs. Regarding model adaptation, traditional methods typically rely on experts manually selecting model types, which is time-consuming and easily influenced by subjective judgment, lacking objectivity and universality. Furthermore, in terms of hydrological situation index construction and early warning triggering mechanisms, existing methods mostly use single parameters or static rules, making it difficult to comprehensively reflect the overall risk situation of the watershed and lacking the ability to flexibly adjust early warning strategies. Therefore, there is an urgent need for a low-code configuration-based hydrological situation analysis and early warning method to achieve more efficient and universal hydrological forecasting and early warning capabilities.

[0023] Figure 1 This is a flowchart of a low-code configuration-based hydrological situation analysis and early warning method according to an embodiment of the present invention. Figure 1 As shown, the hydrological situation analysis and early warning method based on low-code configuration includes, S1: Receives the basic watershed parameters input by the user through a visual configuration interface, standardizes the basic watershed parameters, and generates a watershed feature vector V=[A',L',P'], where the basic watershed parameters include watershed area A, river length L, and historical rainfall threshold P, and A', L', and P' are the standardized watershed area, river length, and rainfall threshold parameters, respectively.

[0024] It should be noted that the unit of drainage area A is square kilometers, the unit of river length L is kilometers, and the unit of historical rainfall threshold P is millimeters per hour.

[0025] S1.1: Receives basic watershed parameters input by the user through the visual configuration interface, performs data type verification and numerical range verification on the basic watershed parameters, and triggers an error message and prompts the user to re-enter the parameters when the basic watershed parameters exceed the preset reasonable range.

[0026] S1.2: Extract the built-in watershed parameter standardization benchmark library to obtain the maximum and minimum benchmark values ​​corresponding to the basic parameters of the watershed.

[0027] S1.3: The basic parameters of the watershed are standardized using the min-max standardization algorithm, and the standardized basic parameters of the watershed are calculated.

[0028] It should be noted that the maximum and minimum benchmark values ​​corresponding to the basic parameters of the watershed include the maximum benchmark value Amax and the minimum benchmark value Amin corresponding to the watershed area A, the maximum benchmark value Lmax and the minimum benchmark value Lmin corresponding to the river length L, and the maximum benchmark value Pmax and the minimum benchmark value Pmin corresponding to the historical rainfall threshold P.

[0029] Preferably, the watershed parameter standardization benchmark library built into the system is extracted, and the watershed area A is standardized using the min-max standardization algorithm to calculate the standardized watershed area A'=(A-Amin) / (Amax-Amin); the same min-max standardization algorithm is used to standardize the channel length L to calculate the channel length L'=(L-Lmin) / (Lmax-Lmin), and the historical rainfall threshold P is standardized to calculate the rainfall threshold parameter P'=(P-Pmin) / (Pmax-Pmin).

[0030] S1.4: Combine the standardized watershed basic parameters in a fixed order to generate a watershed feature vector V=[A',L',P'], and store it in the system cache area. At the same time, display the standardization processing results on the visual configuration interface.

[0031] S2: Based on the watershed feature vector V, a pre-set hydrological model template library is used to match and adapt the model M. The adapted model M determines the optimal hydrological calculation model based on the parameter values ​​in the watershed feature vector V through similarity calculation, and generates a low-code configuration file Config.

[0032] S2.1: Extract all candidate hydrological calculation models from the preset hydrological model template library. Each candidate hydrological calculation model includes a standard watershed feature vector Vs=[As',Ls',Ps'] and the corresponding model parameter set Θs. The standard watershed feature vector Vs serves as the feature identifier for each candidate model.

[0033] Preferably, the candidate hydrological calculation models include: each candidate hydrological calculation model is pre-defined according to the watershed hydrological characteristics; the candidate hydrological calculation models include a small watershed rapid response model, a medium watershed comprehensive response model, and a large watershed delayed response model; the small watershed rapid response model is applicable to watershed characteristics where the standardized watershed area A' ≤ 0.3; the medium watershed comprehensive response model is applicable to watershed characteristics where 0.3 < the standardized watershed area A' ≤ 0.7; and the large watershed delayed response model is applicable to watershed characteristics where the standardized watershed area A' > 0.7.

[0034] Specifically, the standard watershed feature vector Vs of the small watershed rapid response model is set to [0.15, 0.25, 0.35], and the corresponding model parameter set Θs includes runoff coefficient weight αs = 0.8, confluence time weight βs = 0.6 and rainfall response coefficient γs = 1.2. The calculation function f adopts the linear weighted algorithm f = αs × R + βs × H + γs × P'.

[0035] Furthermore, the standard watershed feature vector Vs of the medium-sized watershed integrated response model is set to [0.5, 0.5, 0.5]. The corresponding model parameter set Θs includes runoff coefficient weight αs = 0.6, confluence time weight βs = 0.8, and rainfall response coefficient γs = 1.0. The calculation function f adopts a nonlinear coupling algorithm: f = αs × R × ln(H) + βs × H. 2 +γs×P'×A'.

[0036] Furthermore, the standard watershed feature vector Vs of the large watershed delayed response model is set to [0.85, 0.75, 0.65], and the corresponding model parameter set Θs includes runoff coefficient weight αs = 0.4, confluence time weight βs = 1.0 and rainfall response coefficient γs = 0.8. The calculation function f adopts the time delay correction algorithm f = αs × R(t - Δt) + βs × H × L' + γs × P' × exp(-A').

[0037] It should be noted that the preset hydrological model template library stores the complete configuration information of each candidate hydrological calculation model in XML format, including the standard watershed feature vector Vs, the model parameter set Θs, ​​the algorithm type of the calculation function f, and the configuration of the graded early warning threshold; As', Ls', and Ps' are the standardized watershed area, river length, and rainfall threshold parameters in the candidate hydrological calculation model, respectively.

[0038] S2.2: The Euclidean distance algorithm is used to calculate the similarity score Sim between the watershed feature vector V=[A',L',P'] and the standard watershed feature vector Vs=[As',Ls',Ps'].

[0039] S2.3: Sort the similarity scores Sim of all candidate hydrological calculation models, select the candidate hydrological calculation model with the smallest similarity score Sim as the adapted model M, and obtain the model parameter set Θs and calculation function f corresponding to the adapted model M.

[0040] S2.4: Based on the model structure of the adaptation model M, a basic framework for generating a low-code configuration file Config is generated, which includes a data interface module, a computing engine module, a status module, and an early warning management module.

[0041] S2.5: Embed the calculation function f and the model parameter set Θs into the calculation engine module, and configure the weight allocation strategy for the standardized watershed area A', channel length L', and rainfall threshold parameter P' of the watershed feature vector V=[A',L',P'].

[0042] S2.6: Based on the parameter characteristics of the watershed feature vector V, preset the first-level threshold T1, the second-level threshold T2 and the third-level threshold T3 in the early warning management module, and configure the early warning information template MT1, the first target terminal list LT1, the on-site handling instruction set IT2 and the second target terminal list LT2 associated with each threshold.

[0043] Specifically, each candidate hydrological calculation model is pre-configured with corresponding baseline values ​​for the first-level threshold T1, the second-level threshold T2, and the third-level threshold T3. The thresholds for the small watershed rapid response model are set to T1=0.6, T2=0.8, and T3=1.0; the thresholds for the medium-sized watershed comprehensive response model are set to T1=0.5, T2=0.7, and T3=0.9; and the thresholds for the large watershed delayed response model are set to T1=0.4, T2=0.6, and T3=0.8.

[0044] S2.7: In the data interface module, pre-configure the communication protocol and data format standard for obtaining rainfall data R and water level data H, and in the status module, set a reasonable range for the hydrological situation index WI.

[0045] S3: Input the real-time monitoring rainfall data R and water level data H into the low-code configuration file Config, and calculate the hydrological situation index WI through the adaptation model M.

[0046] S3.1: Obtain real-time rainfall data R and water level data H from the watershed monitoring stations through the data interface module in the low-code configuration file Config. The rainfall data R includes the timestamp TR and the rainfall intensity value IR; the water level data H includes the timestamp TH and the water level height value IH.

[0047] S3.2: Perform time series synchronization verification on real-time rainfall data R and water level data H. When the difference between timestamp TR and timestamp TH is greater than the preset time window ΔT, the data compensation algorithm is triggered to interpolate the data for the missing period.

[0048] S3.3: The synchronously verified rainfall data R and water level data H are fused with the watershed feature vector V=[A',L',P'] to generate a comprehensive input matrix X.

[0049] S3.4: Call the calculation function f in the adaptation model M stored in the low-code configuration file Config, and take the comprehensive input matrix X as the function parameter input. The calculation function f performs weighted calculation on the rainfall data R and water level data H according to the parameter weight allocation strategy in the watershed feature vector V=[A',L',P'].

[0050] S3.5: Calculate the watershed runoff coefficient β and confluence time τ by adapting the hydrological response algorithm built into the model M.

[0051] S3.6: Couple the watershed runoff coefficient β, the runoff time τ, and the standardized rainfall threshold parameter P' to generate the hydrological situation index WI through the calculation function f.

[0052] The preferred formula for the hydrological situation index WI is as follows: ; Wherein, WI is the hydrological situation index representing the current hydrological risk level of the watershed, R is the real-time rainfall intensity value, H is the real-time water level height value, α is the water level response index, with a value of 1.2 used to adjust the nonlinear influence of water level, A' is the standardized watershed area, L' is the standardized channel length, P' is the standardized rainfall threshold parameter, β is the runoff regulation coefficient, τ is the confluence time, γ is the topographic influence factor, σ is the watershed slope coefficient, δ is the hydrological coupling parameter, and λ is the sensitivity adjustment factor.

[0053] It should be noted that the value range of the hydrological situation index WI is [0, 1.2]. Among them, 0 ≤ WI < 0.4 indicates that the hydrological situation of the basin is normal, corresponding to the green safety state; 0.4 ≤ WI < 0.6 indicates that the primary warning state corresponds to the yellow attention level, which requires monitoring of hydrological changes; 0.6 ≤ WI < 0.8 indicates that the intermediate warning state corresponds to the orange warning level, which requires the activation of emergency response strategies; and 0.8 ≤ WI ≤ 1.2 indicates that the advanced warning state corresponds to the red danger level, which requires immediate implementation of emergency warning measures and personnel evacuation.

[0054] S3.7: Store the hydrological condition index WI in the cache area of ​​the low-code configuration file Config, and generate a timestamp identifier TWI.

[0055] S3.8: The validity of the hydrological situation index WI is verified through the status module of the low-code configuration file Config. When the hydrological situation index WI is greater than the preset reasonable range, a data anomaly mark is triggered and the recalculation process is started.

[0056] S4: When the hydrological situation index WI is greater than the preset graded warning threshold, a warning signal is triggered, and warning information is pushed to the designated terminal through the warning strategy predefined in the low-code configuration file Config.

[0057] S4.1: The hydrological situation index WI value and the preset graded warning thresholds are judged, wherein the preset graded warning thresholds include the first level threshold T1, the second level threshold T2 and the third level threshold T3, and satisfy the condition that the first level threshold T1 < the second level threshold T2 < the third level threshold T3.

[0058] It should be noted that the first-level threshold T1 is set as the critical value of the hydrological situation index WI for triggering the primary warning, based on the analysis of the rainfall threshold parameter P' in the watershed feature vector V and the historical hydrological data of the adaptation model M; the second-level threshold T2 is set as the risk value of the hydrological situation index WI for initiating the emergency response strategy, based on the confluence characteristics of the standardized watershed area A' and river length L' in the watershed feature vector V and the watershed runoff coefficient β calculated by the adaptation model M; the third-level threshold T3 is set as the danger value of the hydrological situation index WI for initiating the cross-departmental linkage mechanism and emergency evacuation broadcast, based on the comprehensive risk assessment of the watershed feature vector V and the extreme hydrological simulation of the adaptation model M.

[0059] S4.2: When the hydrological situation index WI value is less than the first-level threshold T1, a primary warning signal is triggered. The primary warning strategy associated with the first-level threshold T1T1 is extracted from the low-code configuration file Config. The primary warning strategy includes the warning information template MT1 and the first target terminal list LT1.

[0060] Preferably, based on the structured fields of the early warning information template MT1, the current watershed feature vector V=[A',L',P'], real-time rainfall data R, and water level data H are filled in to generate a standardized early warning message PT1; through the communication interface integrated in the low-code configuration file Config, the standardized early warning message PT1 is pushed to the mobile terminal of the flood control personnel in a specified data format according to the address information of the first target terminal list LT1.

[0061] S4.3: When the hydrological situation index WI value is greater than or equal to the first-level threshold T1 and less than the second-level threshold T1, the strategy upgrade logic in the low-code configuration file Config will be executed when the intermediate warning signal is triggered.

[0062] Preferably, the strategy upgrade logic includes: while retaining the execution link of the primary early warning strategy, activating the emergency response strategy associated with the second-level threshold T2, wherein the emergency response strategy includes the on-site handling instruction set IT2 and the second target terminal list LT2; binding the on-site handling instruction set IT2 and real-time hydrological data to generate an emergency task package ET2, and synchronously pushing it to the emergency command platform in the second target terminal list LT2 through the government network channel.

[0063] S4.4: When the hydrological situation index WI value is greater than or equal to the second-level threshold T1 and less than the third-level threshold T1, an emergency warning signal is triggered, and the cross-departmental linkage mechanism in the low-code configuration file Config is activated.

[0064] It should be noted that the cross-departmental linkage mechanism includes: extracting the cross-departmental linkage strategy associated with the third-level threshold T3 from the low-code configuration file Config, wherein the cross-departmental linkage strategy includes the third target terminal list LT3, the red warning information template MT3, and the satellite communication instruction set IT3; based on the structured fields of the warning information template MT3, filling in the current basin feature vector V=[A',L',P'], real-time rainfall data R, and water level data H to generate the red warning message PT3; pushing the red warning message PT3 to all terminals in the first target terminal list LT1, the second target terminal list LT2, and the third target terminal list LT3 simultaneously through the communication interface integrated in the low-code configuration file Config; calling the satellite communication module pre-configured in the low-code configuration file Config, and according to the protocol format of the satellite communication instruction set IT3, sending emergency evacuation instructions including basin location information and evacuation routes to the public broadcasting system downstream of the basin through the satellite channel, triggering regional emergency evacuation broadcasts.

[0065] In summary, this invention obtains basic watershed parameters through a visual configuration interface and performs standardized processing to generate a watershed feature vector V=[A',L',P'], achieving data structure standardization and model input uniformity. Based on the watershed feature vector, the Euclidean distance algorithm is used to match the optimal hydrological model, generating a low-code configuration file Config, which enables rapid adaptation of the hydrological model and automatic construction of the computational framework, improving the system's deployment efficiency and customization capabilities. Real-time rainfall and water level data are input into the adapted model M to calculate the hydrological situation index WI, fusing multi-source data and considering watershed parameter weights to achieve accurate quantification of complex hydrological situations. When WI exceeds a preset grading threshold, different levels of early warning information are pushed through predefined strategies in the low-code configuration file, achieving tiered response, automatic linkage, and cross-departmental collaboration, effectively improving the accuracy of early warning and the efficiency of handling sudden hydrological events in the watershed.

[0066] Furthermore, this embodiment also provides a low-code configuration-based hydrological situation analysis and early warning system, including: a feature vector generation module, used to receive watershed basic parameters input by the user through a visual configuration interface, standardize the watershed basic parameters, and generate a watershed feature vector V=[A',L',P'], where the watershed basic parameters include watershed area A, river length L, and historical rainfall threshold P, and A', L', and P' are the standardized watershed area, river length, and rainfall threshold parameters, respectively; and a hydrological model matching and configuration generation module, which matches the watershed feature vector V using a preset hydrological model template library. The system includes an adaptation model M, which determines the optimal hydrological calculation model based on the parameter values ​​in the watershed feature vector V through similarity calculation, and generates a low-code configuration file Config. A hydrological situation calculation module inputs real-time monitored rainfall data R and water level data H into the low-code configuration file Config to calculate the hydrological situation index WI using the adaptation model M. An early warning triggering and information push module triggers an early warning signal when the hydrological situation index WI exceeds a preset graded early warning threshold, and pushes early warning information to designated terminals according to the predefined early warning strategy in the low-code configuration file Config.

[0067] This embodiment also provides a computer device suitable for hydrological situation analysis and early warning methods based on low-code configuration, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the hydrological situation analysis and early warning method based on low-code configuration as proposed in the above embodiment.

[0068] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0069] This embodiment also provides a storage medium storing a computer program. When executed by a processor, the program performs the following steps: receiving basic watershed parameters input by a user through a visual configuration interface, standardizing the basic watershed parameters to generate a watershed feature vector V=[A',L',P'], where the basic watershed parameters include watershed area A, river length L, and historical rainfall threshold P, and A', L', and P' are the standardized watershed area, river length, and rainfall threshold parameters, respectively; based on the watershed feature vector V, matching and adapting a model M using a preset hydrological model template library, where the adapting model M determines the optimal hydrological calculation model based on the parameter values ​​of the watershed feature vector V through similarity calculation, generating a low-code configuration file Config; inputting real-time monitored rainfall data R and water level data H into the low-code configuration file Config, and calculating the hydrological situation index WI through the adapting model M; when the hydrological situation index WI is greater than a preset graded warning threshold, triggering a warning signal, and pushing warning information to a designated terminal through a predefined warning strategy in the low-code configuration file Config.

[0070] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A hydrological situation analysis and early warning method based on low-code configuration, characterized in that: include, The system receives basic watershed parameters input by the user through a visual configuration interface, performs standardization processing on the basic watershed parameters, and generates a watershed feature vector V=[A',L',P']. The basic watershed parameters include watershed area A, river length L, and historical rainfall threshold P, where A', L', and P' are the standardized watershed area, river length, and rainfall threshold parameters, respectively. Based on the watershed feature vector V, a preset hydrological model template library is used to match and adapt the model M. The adapted model M determines the optimal hydrological calculation model based on the parameter values ​​of the watershed feature vector V through similarity calculation, and generates a low-code configuration file Config. The real-time monitoring data of rainfall R and water level H are input into the low-code configuration file Config, and the hydrological situation index WI is calculated through the adaptation model M. When the hydrological situation index WI is greater than the preset graded warning threshold, a warning signal is triggered, and warning information is pushed to the designated terminal through the warning strategy predefined in the low-code configuration file Config.

2. The hydrological situation analysis and early warning method based on low-code configuration as described in claim 1, characterized in that: When the hydrological situation index WI is greater than the preset graded warning threshold, a warning signal is triggered, and warning information is pushed to the designated terminal through the warning strategy predefined in the low-code configuration file Config, including: The hydrological situation index WI value and the preset graded early warning thresholds are judged, wherein the preset graded early warning thresholds include a first-level threshold T1, a second-level threshold T2 and a third-level threshold T3, and satisfy the condition that the first-level threshold T1 < the second-level threshold T2 < the third-level threshold T3. When the hydrological situation index WI value is less than the first-level threshold T1, a primary warning signal is triggered. The primary warning strategy associated with the first-level threshold T1 is extracted from the low-code configuration file Config. The primary warning strategy includes the warning information template MT1 and the first target terminal list LT1. Based on the structured fields of the warning information template MT1, the current watershed feature vector V=[A',L',P'], real-time rainfall data R, and water level data H are filled in to generate a standardized warning message PT1; Through the communication interface integrated in the low-code configuration file Config, the standardized early warning message PT1 is pushed to the mobile terminal of the flood control personnel in a specified data format according to the address information of the first target terminal list LT1; When the hydrological situation index WI value is greater than or equal to the first-level threshold T1 and less than the second-level threshold T1, the intermediate warning signal is triggered, and the strategy upgrade logic in the low-code configuration file Config is executed. When the hydrological situation index WI value is greater than or equal to the second-level threshold T1 and less than the third-level threshold T1, an emergency warning signal is triggered, and the cross-departmental linkage mechanism in the low-code configuration file Config is activated.

3. The hydrological situation analysis and early warning method based on low-code configuration as described in claim 2, characterized in that: The strategy upgrade logic includes: While retaining the execution link of the primary early warning strategy, the emergency response strategy associated with the second-level threshold T2 is activated, wherein the emergency response strategy includes the on-site handling instruction set IT2 and the second target terminal list LT2. The on-site handling instruction set IT2 and real-time hydrological data are bound together to generate an emergency task package ET2, which is then synchronously pushed to the emergency command platform in the second target terminal list LT2 through the government network channel.

4. The hydrological situation analysis and early warning method based on low-code configuration as described in claim 2, characterized in that: The method for obtaining the hydrological situation index WI is as follows: The real-time rainfall data R and water level data H of the watershed monitoring station are obtained through the data interface module in the low-code configuration file Config. The rainfall data R includes a timestamp TR and a rainfall intensity value IR; the water level data H includes a timestamp TH and a water level height value IH. The real-time rainfall data R and the water level data H are synchronized and verified over time. When the difference between the timestamp TR and the timestamp TH is greater than the preset time window ΔT, a data compensation algorithm is triggered to interpolate the data for the missing time period. The synchronously verified rainfall data R and water level data H are fused with the watershed feature vector V=[A',L',P'] to generate a comprehensive input matrix X. The calculation function f in the adaptation model M stored in the low-code configuration file Config is called, and the comprehensive input matrix X is used as the function parameter input. The calculation function f performs weighted calculation on the rainfall data R and the water level data H according to the parameter weight allocation strategy in the watershed feature vector V=[A',L',P']. The watershed runoff coefficient β and the confluence time τ are calculated using the hydrological response algorithm built into the adaptation model M. The watershed runoff coefficient β, the runoff time τ, and the standardized rainfall threshold parameter P' are coupled and calculated to generate the hydrological situation index WI through the calculation function f. The hydrological situation index WI is stored in the cache area of ​​the low-code configuration file Config, and a timestamp identifier TWI is generated at the same time; The validity of the hydrological situation index WI is verified through the status module of the low-code configuration file Config. When the hydrological situation index WI is greater than the preset reasonable range, a data anomaly marker is triggered and the recalculation process is started.

5. The hydrological situation analysis and early warning method based on low-code configuration as described in claim 4, characterized in that: The method for generating the low-code configuration file Config is as follows: All candidate hydrological calculation models are extracted from a pre-set hydrological model template library. Each candidate hydrological calculation model includes a standard watershed feature vector Vs=[As',Ls',Ps'] and a corresponding model parameter set Θs. The standard watershed feature vector Vs serves as the feature identifier for each candidate model. The similarity score Sim between the watershed feature vector V=[A',L',P'] and the standard watershed feature vector Vs=[As',Ls',Ps'] is calculated using the Euclidean distance algorithm. The similarity scores Sim of all candidate hydrological calculation models are sorted, and the candidate hydrological calculation model with the smallest similarity score Sim is selected as the fitting model M. At the same time, the model parameter set Θs and the calculation function f corresponding to the fitting model M are obtained. Based on the model structure of the adaptation model M, a basic framework for generating a low-code configuration file Config is generated, wherein the low-code configuration file Config includes a data interface module, a computing engine module, a status module, and an early warning management module. The calculation function f and the model parameter set Θs are embedded into the calculation engine module, and the weight allocation strategy of the standardized watershed area A', river length L' and rainfall threshold parameter P' of the watershed feature vector V=[A',L',P'] is configured. Based on the parameter characteristics of the watershed feature vector V, a first-level threshold T1, a second-level threshold T2, and a third-level threshold T3 are preset in the early warning management module. At the same time, an early warning information template MT1, a first target terminal list LT1, an on-site handling instruction set IT2, and a second target terminal list LT2 associated with each threshold are configured. The data interface module is pre-configured with communication protocols and data format standards for acquiring the rainfall data R and the water level data H, while the status module sets a reasonable range for the hydrological situation index WI.

6. The hydrological situation analysis and early warning method based on low-code configuration as described in claim 5, characterized in that: The method for obtaining the watershed feature vector is as follows: The system receives basic watershed parameters input by the user through a visual configuration interface, performs data type verification and numerical range verification on the basic watershed parameters, and triggers an error message and prompts the user to re-enter the parameters when the basic watershed parameters exceed a preset reasonable range. Extract the watershed parameter standardization benchmark library built into the system to obtain the maximum and minimum benchmark values ​​corresponding to the basic parameters of the watershed; The watershed basic parameters are standardized using the min-max standardization algorithm, and the standardized watershed basic parameters are calculated. The standardized watershed basic parameters are combined in a fixed order to generate the watershed feature vector V=[A',L',P'], which is then stored in the system cache area. The standardization processing result is displayed on the visualization configuration interface.

7. The hydrological situation analysis and early warning method based on low-code configuration as described in claim 6, characterized in that: The maximum and minimum benchmark values ​​corresponding to the basic parameters of the watershed include the maximum benchmark value Amax and the minimum benchmark value Amin corresponding to the watershed area A, the maximum benchmark value Lmax and the minimum benchmark value Lmin corresponding to the river length L, and the maximum benchmark value Pmax and the minimum benchmark value Pmin corresponding to the historical rainfall threshold P.

8. A hydrological situation analysis and early warning system based on low-code configuration, based on the hydrological situation analysis and early warning method based on low-code configuration according to any one of claims 1 to 7, characterized in that: include, The feature vector generation module is used to receive the basic watershed parameters input by the user through a visual configuration interface, standardize the basic watershed parameters, and generate a watershed feature vector V=[A',L',P'], wherein the basic watershed parameters include watershed area A, river length L, and historical rainfall threshold P, and A', L', and P' are the standardized watershed area, river length, and rainfall threshold parameters, respectively. The hydrological model matching and configuration generation module, based on the watershed feature vector V, uses a preset hydrological model template library to match and adapt the model M. The adapted model M determines the optimal hydrological calculation model based on the parameter values ​​of the watershed feature vector V through similarity calculation, and generates a low-code configuration file Config. The hydrological situation calculation module inputs the real-time monitored rainfall data R and water level data H into the low-code configuration file Config, which is used to calculate the hydrological situation index WI through the adaptation model M. The early warning triggering and information push module is used to trigger an early warning signal when the hydrological situation index WI is greater than the preset graded early warning threshold, and push early warning information to the designated terminal through the early warning strategy predefined in the low-code configuration file Config.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the hydrological situation analysis and early warning method based on low-code configuration as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the hydrological situation analysis and early warning method based on low-code configuration as described in any one of claims 1 to 7.

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