A method and system for predicting a reservoir water level

Abstract

The application discloses a reservoir water level prediction method and system, the method comprising: establishing a mapping relationship between the reservoir water level and the reservoir storage capacity; collecting reservoir basic information, historical rainfall data and historical water level data; calculating a historical runoff coefficient based on the historical rainfall data, the historical water level data, the mapping relationship between the reservoir water level and the reservoir storage capacity and the reservoir basic information; predicting the reservoir storage capacity generated by rainfall according to the estimated rainfall, the reservoir basic information and the historical runoff coefficient; and obtaining a predicted water level after rainfall based on the reservoir basic information, the reservoir storage capacity generated by rainfall and the mapping relationship between the reservoir water level and the reservoir storage capacity. According to the scheme, the runoff coefficient can be dynamically calculated according to the actual hydrological data of the reservoir, the real rainfall-runoff conversion efficiency of the reservoir is reflected, and the calculated historical runoff coefficient can be iteratively optimized as the historical data continuously accumulates, so that the new hydrological conditions are adapted, and the accuracy of the subsequent predicted reservoir water level is higher.

Description

Technical Field

[0001] This application generally relates to the field of water level prediction technology. More specifically, this application relates to a method and system for predicting reservoir water levels. Background Technology

[0002] Reservoirs, as crucial water conservancy infrastructure, play a central role in flood control, disaster reduction, and comprehensive water resource utilization. Reservoir water level prediction is a key reference indicator for flood control scheduling, and its accuracy directly impacts the scientific rigor and timeliness of reservoir scheduling decisions. Current reservoir water level prediction methods are mostly based on historical hydrological data modeling, static parameter assumptions, or single environmental factor analysis. For example, traditional methods estimate water level changes by fixing runoff coefficients or simplifying rainfall-runoff relationships, but these methods still have the following significant shortcomings:

[0003] First, existing methods often neglect the impact of dynamic changes in the reservoir's surrounding environment on water levels. For example, civil engineering projects (such as dam reinforcement and river diversion), changes in vegetation cover, and sudden weather events (such as short-duration heavy rainfall and fluctuations in evaporation rates) can significantly alter the relationship between surface runoff and reservoir storage response. Relying solely on fixed-parameter models will lead to a disconnect between predicted water levels and actual dynamic changes. Second, traditional models often focus on a single driving factor (such as rainfall or discharge volume) and fail to systematically integrate multi-source dynamic data (such as real-time spatiotemporal distribution of rainfall, downstream water demand scheduling, and gate operation strategies). For instance, some methods do not consider the synergistic effect of reservoir scheduling rules and downstream flood control needs in their predictions, resulting in limited applicability of the predictions under complex conditions.

[0004] In view of this, there is an urgent need to provide a reservoir water level prediction scheme to achieve accurate and adaptive water level prediction, and to provide reliable technical support for flood control scheduling and optimal allocation of water resources. Summary of the Invention

[0005] In order to at least solve one or more of the technical problems mentioned above, this application proposes a reservoir water level prediction scheme in several aspects.

[0006] In a first aspect, this application provides a method for predicting reservoir water levels, comprising: establishing a mapping relationship between reservoir water levels and reservoir capacity; collecting basic reservoir information, historical rainfall data, and historical water level data; calculating historical runoff coefficients based on historical rainfall data, historical water level data, the mapping relationship between reservoir water levels and reservoir capacity, and the basic reservoir information; predicting the reservoir capacity generated by rainfall based on estimated rainfall, the basic reservoir information, and the historical runoff coefficients; and obtaining the predicted water level after rainfall based on the basic reservoir information, the reservoir capacity generated by rainfall, and the mapping relationship between reservoir water levels and reservoir capacity.

[0007] In some embodiments, the following steps are performed in the process of calculating the historical runoff coefficient based on historical rainfall data, historical water level data, the mapping relationship between reservoir water level and reservoir capacity, and basic reservoir information: The start and end times of a single rainfall event are identified based on historical rainfall data to form multiple rainfall events corresponding to the historical rainfall data; each rainfall event is divided into multiple rainfall time periods according to a set interval to obtain the rainfall amount within each rainfall time period; the starting and ending reservoir capacities within each rainfall time period are obtained based on historical water level data and the mapping relationship between reservoir water level and reservoir capacity; the runoff coefficient corresponding to each rainfall time period is calculated based on basic reservoir information, the rainfall amount within each rainfall time period, and the starting and ending reservoir capacities within each rainfall time period; the average of the runoff coefficients corresponding to each rainfall event and each rainfall time period is calculated to obtain the runoff coefficient corresponding to each rainfall event, and the average of the runoff coefficients corresponding to each rainfall event is calculated to obtain the historical runoff coefficient.

[0008] In some embodiments, the reservoir basic information includes the current reservoir water level, historical catchment area, current catchment area, and current flood control water level. In calculating the runoff coefficient for each rainfall period based on the reservoir basic information, rainfall amounts during each rainfall period, and the starting and ending reservoir capacities during each rainfall period, the runoff coefficient for each rainfall period is calculated using the runoff coefficient calculation formula based on the historical catchment area, rainfall amounts during each rainfall period, and the starting and ending reservoir capacities during each rainfall period. The runoff coefficient calculation formula is: cof i =(c iend -c istart ) / (s i ×r i ), cof i Let c be the runoff coefficient corresponding to the i-th rainfall period. istart Let c be the initial reservoir capacity during the i-th rainfall period. iend Let s be the final reservoir capacity during the i-th rainfall period. i Let r be the catchment area during the i-th rainfall period. i Let be the rainfall amount during the i-th rainfall period.

[0009] In some embodiments, the historical rainfall data includes historical rainfall amounts and their corresponding timestamps.

[0010] In some embodiments, the historical water level data includes historical water levels and their corresponding timestamps; in the process of obtaining the start and end reservoir capacities for each rainfall period based on historical water level data and the mapping relationship between reservoir water levels and reservoir capacities, the following steps are performed: obtaining the historical water levels corresponding to each rainfall period; obtaining the start and end reservoir capacities for each rainfall period corresponding to the start and end water levels for each rainfall period according to the mapping relationship between reservoir water levels and reservoir capacities.

[0011] In some embodiments, during the process of predicting the reservoir capacity generated by rainfall based on estimated rainfall, reservoir basic information, and historical runoff coefficients, the reservoir capacity generated by rainfall is predicted using a reservoir capacity prediction formula based on estimated rainfall, current catchment area, and historical runoff coefficients; wherein, the reservoir capacity prediction formula is: c f =r f ×s current ×cof p c f r represents the reservoir capacity generated by the predicted rainfall. f To predict rainfall, s current For the current catchment area, cof p This represents the historical runoff coefficient.

[0012] In some embodiments, during the process of obtaining the predicted water level after rainfall based on reservoir basic information, reservoir capacity generated by rainfall, and the mapping relationship between reservoir water level and reservoir capacity, the following steps are performed: obtaining the current reservoir capacity based on reservoir basic information and the mapping relationship between reservoir water level and reservoir capacity; adding the current reservoir capacity and the reservoir capacity generated by rainfall to obtain the total reservoir capacity; and obtaining the predicted water level after rainfall based on the total reservoir capacity and the mapping relationship between reservoir water level and reservoir capacity.

[0013] In some embodiments, after obtaining the predicted water level after rainfall, it is determined whether the predicted water level after rainfall is lower than the current flood control water level; in response to the predicted water level after rainfall being not lower than the current flood control water level, the predicted water level after rainfall is displayed and an alarm message is generated; in response to the predicted water level after rainfall being lower than the current flood control water level, the predicted water level after rainfall is displayed.

[0014] In some embodiments, during the process of establishing the mapping relationship between reservoir water level and reservoir capacity, the accuracy of reservoir water level is split to two decimal places using a binary search algorithm, and a water level-capacity mapping table is generated.

[0015] In a second aspect, this application provides a reservoir water level prediction system, which uses the reservoir water level prediction method as described in any embodiment of the first aspect to predict the reservoir water level. The system includes: a mapping relationship establishment module for establishing a mapping relationship between reservoir water level and reservoir capacity; a data acquisition module for collecting basic reservoir information, historical rainfall data, and historical water level data; a historical runoff coefficient calculation module for calculating historical runoff coefficients based on historical rainfall data, historical water level data, the mapping relationship between reservoir water level and reservoir capacity, and basic reservoir information; a reservoir capacity prediction module for predicting the reservoir capacity generated by rainfall based on estimated rainfall, basic reservoir information, and historical runoff coefficients; and a water level prediction module for obtaining the predicted water level after rainfall based on basic reservoir information, the reservoir capacity generated by rainfall, and the mapping relationship between reservoir water level and reservoir capacity.

[0016] By establishing a quantitative relationship between water level and reservoir capacity, the reservoir water level prediction scheme provided above provides fundamental data support for subsequent calculations of historical runoff coefficients and acquisition of predicted water levels after rainfall. By collecting basic reservoir information, historical rainfall, and water level data, a data foundation is provided for subsequent calculations of historical runoff coefficients, predictions of reservoir capacity generated by rainfall, and acquisition of predicted water levels after rainfall. Compared to the fixed runoff coefficient used in existing technologies, calculating the historical runoff coefficient based on historical rainfall data, historical water level data, the mapping relationship between reservoir water level and reservoir capacity, and basic reservoir information allows for dynamic calculation of the runoff coefficient based on the actual hydrological data of the reservoir. This reflects the reservoir's true rainfall-runoff conversion efficiency, and as historical data accumulates, the calculated historical runoff coefficient can be iteratively optimized to adapt to new hydrological conditions, resulting in higher accuracy in subsequent reservoir water level predictions.

[0017] Furthermore, in some embodiments, during the calculation of historical runoff coefficients, continuous rainfall data is divided into independent rainfall events by identifying the start and end times of individual rainfall events. This facilitates the analysis of the individual impact of each rainfall event on runoff and avoids data contamination. By dividing each rainfall event into multiple time periods according to time intervals, the changes in rainfall intensity over time are captured, thereby more accurately reflecting the dynamic characteristics of the runoff generation process. By combining historical water level data and the reservoir capacity-water level mapping relationship, the changes in reservoir capacity in each time period are derived, quantifying the actual increase or decrease in reservoir water storage and providing a reliable basis for runoff coefficient calculation. Through dynamic tracking of reservoir capacity changes within a time period, the impact of non-rainfall factors such as seepage, evaporation, and human intervention on runoff can be identified, improving adaptability in complex scenarios. By calculating the runoff coefficient by time period and then averaging it to obtain the runoff coefficient corresponding to each rainfall event, and averaging the runoff coefficients corresponding to each rainfall event, outliers in a single time period can be effectively smoothed, making the obtained historical runoff coefficients more robust.

[0018] Furthermore, in some embodiments, after obtaining the predicted water level after rainfall, the system can promptly issue an alarm indicating excessively high water levels by determining the relationship between the predicted water level and the current flood control water level. This helps to take preventative flood control measures in advance and avoid floods or disasters caused by heavy rain. Simultaneously, regardless of whether the predicted water level is higher or lower than the flood control water level, the system will display the prediction results to relevant personnel, ensuring information transparency and helping decision-makers make more informed decisions. Attached Figure Description

[0019] The above and other objects, features, and advantages of exemplary embodiments of this application will become readily understood by reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of this application are illustrated by way of example and not limitation, and the same or corresponding reference numerals denote the same or corresponding parts, wherein:

[0020] Figure 1 An exemplary flowchart of a method for predicting reservoir water levels according to an embodiment of this application is shown;

[0021] Figure 2 An exemplary flowchart illustrating the calculation of historical runoff coefficients according to an embodiment of this application is shown;

[0022] Figure 3 An exemplary flowchart illustrating the acquisition of predicted water levels after rainfall, according to an embodiment of this application, is shown.

[0023] Figure 4 An exemplary flowchart illustrating an embodiment of this application for issuing an early warning of excessively high water levels based on the relationship between the predicted water level after rainfall and the current flood control water level;

[0024] Figure 5 An exemplary structural block diagram of a reservoir water level prediction system according to an embodiment of this application is shown. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0026] It should be understood that the terms "comprising" and "including" as used in the specification and claims of this application indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0027] It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application. As used in this specification and claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this specification and claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations.

[0028] Figure 1 An exemplary flowchart of a reservoir water level prediction method 100 according to an embodiment of this application is shown.

[0029] like Figure 1 As shown, in step S110, a mapping relationship between the reservoir water level and the reservoir capacity is established.

[0030] In the embodiments of this application, in the process of establishing the mapping relationship between reservoir water level and reservoir capacity, the accuracy of reservoir water level is split to two decimal places by a binary search algorithm, and a water level-capacity mapping table is generated.

[0031] Specifically, in the process of refining the reservoir water level accuracy to two decimal places using the binary search algorithm, the first step is to establish the reservoir water level (unit: meters) and reservoir capacity (unit: meters). 3 The corresponding relationship table or function model (e.g., polynomial fitting, lookup table method, or measured data interpolation) is used. This relationship is ensured to be a monotonically increasing function within the target interval to satisfy the application conditions of the bisection method. Next, based on actual needs, the upper and lower limits of the reservoir water level are defined to ensure that the target reservoir capacity value lies within the corresponding reservoir capacity range of the water level interval. Then, the bisection algorithm is iteratively executed to obtain the midpoint water level. Finally, the midpoint water level of the last iteration is used as the result, ensuring that it satisfies |c... mid -c target | Within the allowable error range. Where, c mid c represents the reservoir capacity corresponding to the midpoint water level. target The target storage capacity value.

[0032] Specifically, in the process of iteratively executing the binary search algorithm to obtain the midpoint water level, firstly, the midpoint water level h of the reservoir water level interval is calculated. mid =(h min +h max ) / 2, rounded to two decimal places (e.g., 125.00m), where h mid h represents the water level at the midpoint of the reservoir's water level range. min h represents the lower limit of the reservoir water level. max This represents the upper limit of the reservoir's water level. Next, based on the water level-reservoir capacity relationship, the midpoint water level h is obtained. mid The corresponding storage capacity cmid Then, compare c. mid With c target If c mid <c target Then update the lower limit of the reservoir water level so that h min =h mid If c mid >c target Then update the upper limit of the reservoir water level, so that h max =h mid If c mid =c target Then output h directly. mid Repeat the above steps until the reservoir water level interval is h. max -h min <0.01 means that the precision is satisfied to two decimal places.

[0033] In one embodiment of this application, the target library capacity value c to be searched is... target =500000m 3 The process of obtaining the corresponding precise reservoir water level value is as follows: First, the reservoir water level range is set to [100m, 150m]. Then, the binary search algorithm is executed iteratively. In the first iteration, h... mid =125.00m, corresponding to c mid =480000m 3 Because of c mid <c target At this point, update h min =125.00m. During the second iteration, the new reservoir water level range is [125.00m, 150.00m], h mid =137.50m, corresponding to c mid =520000m 3 Because of c mid >c target At this point, update h min =137.50m. Continue iterating until the reservoir water level range is less than 0.01m, and finally obtain h. mid =132.81m, corresponding to a reservoir capacity of 500,000m³. 3 .

[0034] By using the binary search method, the accuracy of reservoir water level was improved to two decimal places (0.01m level), which solved the accuracy loss problem of traditional methods in discrete data scenarios.

[0035] By setting an iteration termination condition (such as h) max -h min <0.01m), directly controlling the accuracy of the results, the error range decreases exponentially with the number of iterations (the error is halved with each iteration).

[0036] After completing step S110, in step S120, basic information about the reservoir, historical rainfall data, and historical water level data are collected.

[0037] In the embodiments of this application, the basic information of the reservoir includes the current reservoir water level, historical catchment area, current catchment area, and current flood control water level.

[0038] In the embodiments of this application, the current flood control water level is set according to actual needs and historical experience, and this application does not impose any restrictions on it.

[0039] In the embodiments of this application, historical rainfall data includes historical rainfall amounts and their corresponding timestamps.

[0040] In the embodiments of this application, historical water level data includes historical water levels and their corresponding timestamps.

[0041] By collecting basic information about reservoirs, historical rainfall data, and historical water level data, we can provide a data foundation for calculating the historical runoff coefficient and obtaining the predicted water level after rainfall.

[0042] After completing step S120, in step S130, the historical runoff coefficient is calculated based on historical rainfall data, historical water level data, the mapping relationship between reservoir water level and reservoir capacity, and basic reservoir information.

[0043] In the embodiments of this application, the specific steps involved in step S130 can be found in the following references. Figure 2 .

[0044] Figure 2 An exemplary flowchart illustrating the calculation of historical runoff coefficients according to an embodiment of this application is shown.

[0045] like Figure 2 As shown, in step S210, the start and end times of a single rainfall event are identified based on historical rainfall data, forming multiple rainfall events corresponding to the historical rainfall data. In step S220, each rainfall event is divided into multiple rainfall time periods according to a set interval to obtain the rainfall amount within each rainfall time period. In step S230, the starting and ending reservoir capacities for each rainfall time period are obtained based on historical water level data and the mapping relationship between reservoir water level and reservoir capacity. In step S240, the runoff coefficient corresponding to each rainfall time period is calculated based on the reservoir basic information, the rainfall amount within each rainfall time period, and the starting and ending reservoir capacities within each rainfall time period. In step S250, the average value of the runoff coefficients corresponding to each rainfall event and each rainfall time period is calculated to obtain the runoff coefficient for each rainfall event, and the average value of the runoff coefficients corresponding to each rainfall event is calculated to obtain the historical runoff coefficient.

[0046] In the embodiments of this application, during step S210, the historical rainfall data is first cleaned. This cleaning process includes handling missing values ​​and correcting outliers. For example, missing values ​​are handled by interpolation or deletion of invalid historical rainfall data, and outliers are corrected by removing negative rainfall data or extreme value data. Next, a rainfall threshold and a minimum dry period are set. Then, the cleaned historical rainfall data is iterated according to its corresponding timestamp, and the historical rainfall data is divided into multiple rainfall events based on the rainfall threshold and the minimum dry period, with the start and end times of each rainfall event marked. When the rainfall amount is greater than the rainfall threshold, it is determined to be a rainfall event. If the longest dry period between two rainfall events is greater than or equal to the minimum dry period, they are considered two independent rainfall events.

[0047] In the embodiments of this application, the rainfall threshold and the longest rainless time between two rainfalls are set according to actual needs and historical experience, and this application does not impose any restrictions on them.

[0048] In the embodiments of this application, the aforementioned interval time is set according to actual needs and historical experience, and this application does not impose any restrictions on it. For example, in some embodiments, the interval time is 15 minutes.

[0049] In the embodiments of this application, during step S230, firstly, the historical water levels corresponding to each rainfall period are obtained. Then, based on the mapping relationship between reservoir water levels and reservoir capacity, the starting and ending reservoir capacities corresponding to the starting and ending water levels for each rainfall period are obtained.

[0050] Specifically, since historical water level data includes historical water levels and their corresponding timestamps, obtaining the historical water levels for each rainfall period is as simple as matching the timestamps of the historical water levels with the respective rainfall periods. This allows for a clear understanding of the temporal relationship between rainfall events and water level changes simply by aligning the timestamps, eliminating other interfering factors (such as man-made flood discharges or upstream water releases), and thus enabling a more reliable analysis of the direct impact of rainfall on water levels.

[0051] In the embodiments of this application, during the execution of step S240, the runoff coefficient corresponding to each rainfall period is calculated using the runoff coefficient calculation formula based on the historical catchment area, the rainfall in each rainfall period, and the starting and ending reservoir capacity in each rainfall period.

[0052] Specifically, the formula for calculating the runoff coefficient is: cof i =(c iend -c istart ) / (s i ×ri ), cof i Let c be the runoff coefficient corresponding to the i-th rainfall period. istart Let c be the initial reservoir capacity during the i-th rainfall period. iend Let s be the final reservoir capacity during the i-th rainfall period. i Let r be the catchment area during the i-th rainfall period. i Let be the rainfall amount during the i-th rainfall period.

[0053] In the embodiments of this application, by executing step S250, the runoff coefficient of a single rainfall event at different time periods may vary significantly due to factors such as rainfall intensity and soil infiltration capacity. Averaging across different time periods can more reasonably synthesize the runoff characteristics of the entire rainfall event, avoiding the neglect of dynamic changes over time. By averaging the runoff coefficients at different time periods within a single rainfall event and the runoff coefficients corresponding to different rainfall events across multiple events, the interference of a single extreme rainfall event or outliers at a certain time period on the overall results can be effectively reduced, making the results more statistically robust.

[0054] After completing step S130, in step S140, the reservoir capacity generated by rainfall is predicted based on the estimated rainfall, basic reservoir information, and historical runoff coefficient.

[0055] In the embodiments of this application, in the process of predicting the reservoir capacity generated by rainfall based on estimated rainfall, reservoir basic information and historical runoff coefficient, the reservoir capacity generated by rainfall is predicted by the reservoir capacity prediction formula based on the estimated rainfall, the current catchment area in the reservoir basic information and the historical runoff coefficient.

[0056] In the embodiments of this application, the aforementioned estimated rainfall is obtained based on weather forecasts, etc., and this application does not impose any restrictions on it.

[0057] Specifically, the formula for predicting reservoir capacity is: c f =r f ×s current ×cof p c f r represents the reservoir capacity generated by the predicted rainfall. f To predict rainfall, s current For the current catchment area, cof p This represents the historical runoff coefficient.

[0058] After completing step S140, in step S150, the predicted water level after rainfall is obtained based on the reservoir's basic information, the reservoir capacity generated by rainfall, and the mapping relationship between the reservoir water level and the reservoir capacity.

[0059] In the embodiments of this application, the specific steps involved in step S150 can be found in [reference needed]. Figure 3 .

[0060] Figure 3 An exemplary flowchart illustrating the acquisition of predicted water levels after rainfall, according to an embodiment of this application, is shown.

[0061] like Figure 3 As shown, in step S310, the current reservoir capacity is obtained based on the reservoir's basic information and the mapping relationship between reservoir water level and reservoir capacity. In step S320, the current reservoir capacity and the reservoir capacity generated by rainfall are added together to obtain the total reservoir capacity. In step S330, the predicted water level after rainfall is obtained based on the total reservoir capacity and the mapping relationship between reservoir water level and reservoir capacity.

[0062] In the embodiments of this application, in the process of obtaining the current reservoir capacity based on the reservoir basic information and the mapping relationship between reservoir water level and reservoir capacity, the current reservoir water level in the reservoir basic information is substituted into the mapping relationship between reservoir water level and reservoir capacity to obtain the current reservoir capacity.

[0063] In the embodiments of this application, after obtaining the predicted water level after rainfall, a high water level warning is issued based on the relationship between the obtained predicted water level after rainfall and the current flood control water level in the reservoir's basic information. For details, please refer to [link / reference needed]. Figure 4 .

[0064] Figure 4 An exemplary flowchart of an embodiment of this application is shown, which provides an early warning of excessively high water levels based on the relationship between the predicted water level after rainfall and the current flood control water level.

[0065] like Figure 4 As shown, in step S410, it is determined whether the predicted water level after rainfall is lower than the current flood control water level. In response to the predicted water level after rainfall not being lower than the current flood control water level, in step S420, the predicted water level after rainfall is displayed, and an alarm message is generated. In response to the predicted water level after rainfall being lower than the current flood control water level, in step S430, the predicted water level after rainfall is displayed.

[0066] In the embodiments of this application, the alarm information may include the difference between the predicted water level after rainfall and the current flood control water level, the alarm level, etc., which are not limited here.

[0067] Specifically, the aforementioned alarm level can be obtained based on the threshold range of the difference between the predicted water level after rainfall and the current flood control water level.

[0068] Whether the predicted water level is higher or lower than the flood control level, the system will display the prediction results to relevant personnel, ensuring information transparency and helping decision-makers make more informed decisions.

[0069] In summary, through the reservoir water level prediction scheme provided above, this application embodiment establishes a quantitative relationship between water level and reservoir capacity, providing fundamental data support for subsequent calculation of historical runoff coefficients and acquisition of predicted water levels after rainfall. By collecting basic reservoir information, historical rainfall, and water level data, a data foundation is provided for subsequent calculation of historical runoff coefficients, prediction of reservoir capacity generated by rainfall, and acquisition of predicted water levels after rainfall. By calculating historical runoff coefficients based on historical rainfall data, historical water level data, the mapping relationship between reservoir water level and reservoir capacity, and basic reservoir information, compared to the fixed runoff coefficients used in existing technologies, the runoff coefficients can be dynamically calculated based on the actual hydrological data of the reservoir, reflecting the true rainfall-runoff conversion efficiency of the reservoir. Furthermore, as historical data accumulates, the calculated historical runoff coefficients can be iteratively optimized to adapt to new hydrological conditions, resulting in higher accuracy in subsequent reservoir water level predictions.

[0070] Furthermore, in some embodiments, during the calculation of historical runoff coefficients, continuous rainfall data is divided into independent rainfall events by identifying the start and end times of individual rainfall events. This facilitates the analysis of the individual impact of each rainfall event on runoff and avoids data contamination. By dividing each rainfall event into multiple time periods according to time intervals, the changes in rainfall intensity over time are captured, thereby more accurately reflecting the dynamic characteristics of the runoff generation process. By combining historical water level data and the reservoir capacity-water level mapping relationship, the changes in reservoir capacity in each time period are derived, quantifying the actual increase or decrease in reservoir water storage and providing a reliable basis for runoff coefficient calculation. Through dynamic tracking of reservoir capacity changes within a time period, the impact of non-rainfall factors such as seepage, evaporation, and human intervention on runoff can be identified, improving adaptability in complex scenarios. By calculating the runoff coefficient by time period and then averaging it to obtain the runoff coefficient corresponding to each rainfall event, and averaging the runoff coefficients corresponding to each rainfall event, outliers in a single time period can be effectively smoothed, making the obtained historical runoff coefficients more robust.

[0071] Furthermore, in some embodiments, after obtaining the predicted water level after rainfall, the system can promptly issue an alarm indicating excessively high water levels by determining the relationship between the predicted water level and the current flood control water level. This helps to take preventative flood control measures in advance and avoid floods or disasters caused by heavy rain. Simultaneously, regardless of whether the predicted water level is higher or lower than the flood control water level, the system will display the prediction results to relevant personnel, ensuring information transparency and helping decision-makers make more informed decisions.

[0072] This application also provides a reservoir water level prediction system, which can use the aforementioned reservoir water level prediction method 100 to predict the reservoir water level, or other methods can be used to predict the reservoir water level. This application does not impose any restrictions on this method.

[0073] Figure 5 An exemplary structural block diagram of a reservoir water level prediction system according to an embodiment of this application is shown.

[0074] like Figure 5 As shown, the system 500 includes a mapping relationship establishment module 510, a data acquisition module 520, a historical runoff coefficient calculation module 530, a reservoir capacity prediction module 540, and a water level prediction module 550. In the embodiments of this application, the mapping relationship establishment module 510, the data acquisition module 520, the historical runoff coefficient calculation module 530, the reservoir capacity prediction module 540, and the water level prediction module 550 can be separate units or integrated into the same integrated circuit; this application does not impose any restrictions here.

[0075] Specifically, the mapping relationship establishment module 510 is used to establish the mapping relationship between reservoir water level and reservoir capacity.

[0076] Specifically, the data acquisition module 520 is used to collect basic information about the reservoir, historical rainfall data, and historical water level data.

[0077] Specifically, the historical runoff coefficient calculation module 530 is used to calculate the historical runoff coefficient based on historical rainfall data, historical water level data, the mapping relationship between reservoir water level and reservoir capacity, and basic reservoir information.

[0078] Specifically, the reservoir capacity prediction module 540 is used to predict the reservoir capacity generated by rainfall based on estimated rainfall, basic reservoir information, and historical runoff coefficients.

[0079] Specifically, the water level prediction module 550 is used to obtain the predicted water level after rainfall based on the reservoir's basic information, the reservoir capacity generated by rainfall, and the mapping relationship between the reservoir water level and the reservoir capacity.

[0080] When system 500 uses the aforementioned reservoir water level prediction method 100 to predict the reservoir water level, the mapping relationship establishment module 510 executes the aforementioned step S110, the data acquisition module 520 executes the aforementioned step S120, the historical runoff coefficient calculation module 530 executes the aforementioned step S130, the reservoir capacity prediction module 540 executes the aforementioned step S140, and the water level prediction module 550 executes the aforementioned step S150. The specific execution process can be found above and will not be repeated here.

[0081] While numerous embodiments of this application have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Many modifications, alterations, and alternatives will arise for those skilled in the art without departing from the spirit and intent of this application. It should be understood that various alternatives to the embodiments of this application described herein may be employed in the practice of this application. The appended claims are intended to define the scope of protection of this application and therefore cover equivalents or alternatives within the scope of these claims.

Claims

1. A method for predicting reservoir water levels, characterized in that, include: Establish a mapping relationship between reservoir water level and reservoir capacity; Collect basic information about the reservoir, historical rainfall data, and historical water level data; Historical runoff coefficients are calculated based on historical rainfall data, historical water level data, the mapping relationship between reservoir water level and reservoir capacity, and basic reservoir information. Predict the reservoir capacity generated by rainfall based on estimated rainfall, basic reservoir information, and historical runoff coefficients; The predicted water level after rainfall is obtained based on basic reservoir information, reservoir capacity generated by rainfall, and the mapping relationship between reservoir water level and reservoir capacity. The following steps are performed in the process of calculating the historical runoff coefficient based on historical rainfall data, historical water level data, the mapping relationship between reservoir water level and reservoir capacity, and basic reservoir information: Identify the start and end times of a single rainfall event based on historical rainfall data to generate multiple rainfall events corresponding to the historical rainfall data; Each rainfall event is divided into multiple rainfall periods according to a set interval, so as to obtain the rainfall amount in each rainfall period; Based on historical water level data and the mapping relationship between reservoir water level and reservoir capacity, the starting and ending reservoir capacities for each rainfall period are obtained. Calculate the runoff coefficient for each rainfall period based on the reservoir's basic information, the rainfall amount during each rainfall period, and the reservoir's initial and final storage capacities during each rainfall period. The average value of the runoff coefficients for each rainfall event across all rainfall periods is used to obtain the runoff coefficient for each rainfall event. The average value of the runoff coefficients for each rainfall event is then used to obtain the historical runoff coefficient.

2. The method for predicting reservoir water levels according to claim 1, characterized in that, The basic information about the reservoir includes the current reservoir water level, historical catchment area, current catchment area, and current flood control water level; In the process of calculating the runoff coefficient corresponding to each rainfall period based on the basic information of the reservoir, the rainfall in each rainfall period, and the starting and ending reservoir capacity in each rainfall period, the runoff coefficient corresponding to each rainfall period is calculated based on the historical catchment area, the rainfall in each rainfall period, and the starting and ending reservoir capacity in each rainfall period using the runoff coefficient calculation formula. The formula for calculating the runoff coefficient is: cof i =(c iend -c istart ) / (s i ×r i ), cof i Let c be the runoff coefficient corresponding to the i-th rainfall period. istart Let c be the initial reservoir capacity during the i-th rainfall period. iend Let s be the final reservoir capacity during the i-th rainfall period. i Let r be the catchment area during the i-th rainfall period. i Let be the rainfall amount during the i-th rainfall period.

3. The method for predicting reservoir water levels according to claim 1, characterized in that, The historical rainfall data includes historical rainfall amounts and their corresponding timestamps.

4. The method for predicting reservoir water levels according to claim 1, characterized in that, The historical water level data includes historical water levels and their corresponding timestamps; In obtaining the starting and ending reservoir capacities for each rainfall period based on historical water level data and the mapping relationship between reservoir water level and reservoir capacity, the following steps are performed: Obtain the historical water levels corresponding to each rainfall period; Based on the mapping relationship between reservoir water level and reservoir capacity, the starting and ending water levels for each rainfall period are obtained, along with the corresponding starting and ending reservoir capacities for each rainfall period.

5. The method for predicting reservoir water levels according to claim 2, characterized in that, In the process of predicting the reservoir capacity generated by rainfall based on estimated rainfall, basic reservoir information and historical runoff coefficient, the reservoir capacity generated by rainfall is predicted using the reservoir capacity prediction formula based on estimated rainfall, current catchment area and historical runoff coefficient. The reservoir capacity prediction formula is: c f =r f ×s current ×cof p c f r represents the reservoir capacity generated by the predicted rainfall. f To predict rainfall, s current For the current catchment area, cof p This represents the historical runoff coefficient.

6. The method for predicting reservoir water levels according to claim 1, characterized in that, In the process of obtaining the predicted water level after rainfall based on basic reservoir information, reservoir capacity generated by rainfall, and the mapping relationship between reservoir water level and reservoir capacity, the following steps are performed: The current reservoir capacity is obtained based on the reservoir's basic information and the mapping relationship between the reservoir's water level and its capacity. The total reservoir capacity is obtained by adding the current reservoir capacity and the reservoir capacity generated by rainfall. The predicted water level after rainfall is obtained based on the total reservoir capacity and the mapping relationship between reservoir water level and reservoir capacity.

7. The method for predicting reservoir water levels according to claim 2, characterized in that, After obtaining the predicted water level after rainfall, determine whether the predicted water level after rainfall is lower than the current flood control water level; In response to the situation where the predicted water level after rainfall is not lower than the current flood control water level, the predicted water level after rainfall is displayed and an alarm message is generated; In response to the predicted water level after rainfall being lower than the current flood control water level, the predicted water level after rainfall is displayed.

8. The method for predicting reservoir water levels according to claim 1, characterized in that, In establishing the mapping relationship between reservoir water level and reservoir capacity, a binary search algorithm is used to split the accuracy of reservoir water level to two decimal places and generate a water level-capacity mapping table.

9. A reservoir water level prediction system, characterized in that, Using reservoir water as described in any one of claims 1-8 The system includes a method for predicting reservoir water levels, comprising: The mapping relationship establishment module is used to establish the mapping relationship between reservoir water level and reservoir capacity; The data acquisition module is used to collect basic information about the reservoir, historical rainfall data, and historical water level data. The historical runoff coefficient calculation module is used to calculate the historical runoff coefficient based on historical rainfall data, historical water level data, the mapping relationship between reservoir water level and reservoir capacity, and basic reservoir information. The reservoir capacity prediction module is used to predict the reservoir capacity generated by rainfall based on estimated rainfall, basic reservoir information, and historical runoff coefficients. The water level prediction module is used to obtain the predicted water level after rainfall based on the reservoir's basic information, the reservoir capacity generated by rainfall, and the mapping relationship between the reservoir water level and the reservoir capacity. The following steps are performed in the process of calculating the historical runoff coefficient based on historical rainfall data, historical water level data, the mapping relationship between reservoir water level and reservoir capacity, and basic reservoir information: Identify the start and end times of a single rainfall event based on historical rainfall data to generate multiple rainfall events corresponding to the historical rainfall data; Each rainfall event is divided into multiple rainfall periods according to a set interval, so as to obtain the rainfall amount in each rainfall period; Based on historical water level data and the mapping relationship between reservoir water level and reservoir capacity, the starting and ending reservoir capacities for each rainfall period are obtained. Calculate the runoff coefficient for each rainfall period based on the reservoir's basic information, the rainfall amount during each rainfall period, and the reservoir's initial and final storage capacities during each rainfall period. The average value of the runoff coefficients for each rainfall event across all rainfall periods is used to obtain the runoff coefficient for each rainfall event. The average value of the runoff coefficients for each rainfall event is then used to obtain the historical runoff coefficient.

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