Method and device for estimating river network storage capacity, electronic equipment and storage medium

Abstract

The application discloses a kind of river network storage capacity estimation method, device, electronic equipment and storage medium, the method includes: obtaining planar river network data and the historical water level data of multiple hydrological stations, and linear river network data is drawn based on the center of the planar river network data;The planar river network data and the linear river network data are carried out fishing net division, obtain multiple different river network units, and determine the river network loop ratio of different river network units based on the linear river network data;Based on the historical water level data, calculate the Hurst index for representing the storage capacity of the region controlled by hydrological station;Establish the linear regression model between the Hurst index and the river network loop ratio of the river network unit where the hydrological station is located;The river network loop ratio of different river network units is input into the linear regression model, and the Hurst index for representing the storage capacity of different river network units is obtained.The technical scheme provided by the application can improve the accuracy of kilometer scale river network unit storage capacity estimation.

Description

Technical Field

[0001] This invention relates to the field of data processing, and specifically to a method, apparatus, electronic device, and storage medium for estimating the water storage capacity of a river network. Background Technology

[0002] River network regulation capacity is mostly described by static indicators related to storage capacity. However, with the exploration of river network regulation capacity from static quantities to dynamic processes, indicators such as adjustable storage capacity per unit area have emerged, providing a dynamic description of the hydrological regulation process. Furthermore, existing research has demonstrated that adjustable storage capacity per unit area is more suitable as a direct indicator for flood regulation than channel storage capacity per unit area. Currently, most empirical studies in urban plain river networks in my country still use indicators related to channel storage capacity. While this is applicable for studying and managing changes over decades at the spatial scale of watersheds or urban agglomerations, its effectiveness is limited for studying low- to medium-level river networks within cities, making it difficult to meet the needs of refined management. Summary of the Invention

[0003] In view of this, the present invention provides a method, apparatus, electronic device and storage medium for estimating the river network regulation capacity, which can improve the accuracy of river network regulation capacity estimation to a certain extent.

[0004] This invention provides a method for estimating the storage capacity of a river network. The method includes: acquiring isometric river network data and historical water level data from multiple hydrological stations, and drawing linear river network data based on the center of the isometric river network data; dividing the isometric river network data / linear river network data into multiple different river network units, and determining the river network ring ratio of different river network units based on the linear river network data; calculating the Hurst index to characterize the storage capacity of the area controlled by the hydrological station based on the historical water level data; establishing a linear regression model between the Hurst index to characterize the storage capacity of the hydrological station and the river network ring ratio of the river network unit where the hydrological station is located; and inputting the river network ring ratio of different river network units into the linear regression model to obtain the Hurst index to characterize the storage capacity of different river network units.

[0005] In one embodiment, determining the ring ratio of different river network units based on the linear river network data includes: obtaining the number of rings and the number of connected river networks for different river network units respectively; and dividing the number of rings by the number of connected river networks to obtain the ring ratio of the river network.

[0006] In one embodiment, calculating the Hearst index, which characterizes the storage capacity of the area controlled by the hydrological station, based on the historical water level data includes: dividing the historical water level data into multiple historical water level data subsets; calculating the mean of the ratio of the range to the standard deviation of the multiple historical water level data subsets to obtain the Hearst index characterizing the storage capacity of the area controlled by the hydrological station.

[0007] In one embodiment, the historical hydrological data includes continuous daily hydrological data from multiple years, and the method further includes: calculating the Hurst index, which characterizes the storage capacity of the area controlled by the hydrological station for multiple years; and averaging the Hurst indices from multiple years to obtain the average Hurst index.

[0008] In one embodiment, drawing linear river network data based on the center of the isometric river network data includes: calculating the average river width of each river in the isometric river network data; if the average river width is greater than or equal to a preset threshold, then extracting the centerline of the river as linear river network data.

[0009] In one embodiment, the method for estimating the river network's regulation capacity further includes: if the coordinate system of the isometric river network data is a geographic coordinate system, then converting the isometric river network data into a projected coordinate system.

[0010] In one embodiment, the method for estimating the river network's storage capacity further includes: statistically analyzing the river network density, surface area ratio, number of nodes, and number of river chains for different river network units based on the areal river network data and the linear river network data; calculating the connectivity and circulation degree of different river network units based on the number of nodes and the number of river chains; and analyzing the correlation between the river network density, surface area ratio, connectivity, circulation degree, and river network storage capacity.

[0011] In another aspect, the present invention provides a river network regulation capacity estimation device, comprising: a data acquisition unit for acquiring isometric river network data and historical water level data from multiple hydrological stations, and drawing linear river network data based on the center of the isometric river network data; a river network unit for dividing the isometric river network data / linear river network data into multiple different river network units, and determining the river network ratio of different river network units based on the linear river network data; a hydrological station regulation capacity calculation unit for calculating the Hurst index, which characterizes the regulation capacity of the area controlled by the hydrological station, based on the historical water level data; a model building unit for establishing a linear regression model between the Hurst index, which characterizes the regulation capacity of the hydrological station, and the river network ratio of the river network unit where the hydrological station is located; and a river network regulation capacity estimation unit for inputting the river network ratios of different river network units into the linear regression model to obtain the Hurst index, which characterizes the regulation capacity of different river network units.

[0012] In another aspect, the present invention provides an electronic device, the electronic device comprising a processor and a memory, the memory being used to store a computer program, which, when executed by the processor, implements the above-described method for estimating the river network regulation capacity.

[0013] In another aspect, the present invention provides a computer-readable storage medium for storing a computer program that, when executed by a processor, implements the above-described method for estimating the river network regulation capacity.

[0014] By calculating the Hearst index of historical water level data of hydrological stations and establishing a linear regression model with the chain ratio of the river network in the area controlled by the hydrological station, the linear regression relationship between the Hearst index, which characterizes the river network's storage capacity, and the chain ratio of the river network is obtained. Finally, the chain ratio of the river network of different river network units is substituted into the linear regression model for calculation to obtain the storage capacity of different river network units, thereby improving the accuracy of storage capacity estimation to a certain extent. Attached Figure Description

[0015] The features and advantages of the invention will be more clearly understood by referring to the accompanying drawings, which are schematic and should not be construed as limiting the invention in any way. In the drawings:

[0016] Figure 1 A flowchart illustrating a method for estimating river network storage capacity according to one embodiment of the present invention is shown.

[0017] Figure 2 A schematic diagram of a river network regulation and storage capacity estimation device according to one embodiment of the present invention is shown.

[0018] Figure 3 A schematic diagram of the structure of an electronic device according to one embodiment of the present invention is shown. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] For a long time, the regulation capacity of river networks has been mostly described by static indicators related to storage capacity. However, with the exploration of river network regulation capacity from static quantities to dynamic processes, indicators such as adjustable storage capacity per unit area have begun to emerge, providing a dynamic description of the hydrological regulation process. Furthermore, studies have shown that adjustable storage capacity per unit area is more suitable as a direct indicator of flood regulation than channel storage capacity per unit area. Most empirical studies in urban areas of my country's plain river networks still use indicators related to channel storage capacity. This is applicable to studies of changes over decades at the basin or urban agglomeration scale, but its effectiveness is limited when studying low- to medium-level river networks within cities.

[0021] On the other hand, some scholars have proposed the possibility of assessing the river network's regulation capacity using two types of indicators: water surface area and river structure. However, this method describes the spatial morphology and struggles to provide a mechanistic explanation for flow capacity and water level changes. Meanwhile, some indicators can describe the regulation capacity of lateral and longitudinal flow, such as the annual average runoff guarantee rate, river flow, river water level, and average flow velocity. However, these indicators have different starting points, their relationships are difficult to define, and some data are hard to obtain.

[0022] Urbanization has severely degraded the natural structure and water storage function. Low-grade rivers (10-40 meters wide) have a significant role in flood control, but in my country's plain cities, river networks have been neglected during the urbanization process, resulting in severe degradation of their natural structure and water storage function. Currently, the planning and management of urban water systems has entered a stage of refinement. Water system management and planning design based on river network morphology parameters such as water surface ratio, river network density, connectivity, and circulation requires multi-scale and multi-dimensional basis.

[0023] Water level and storage capacity are related concepts. After calculations using graded river parameters and water levels under specific conditions, the indicators related to storage capacity often reflect changes over a relatively long period. However, by estimating using a continuous water level change curve, short-term changes can be reflected.

[0024] Please see Figure 1 One embodiment of this application provides a method for estimating the river network's water storage capacity, which may include the following steps.

[0025] S110: Obtain isometric river network data and historical water level data from multiple hydrological stations, and draw linear river network data based on the center of the isometric river network data.

[0026] In this embodiment, water conservancy units such as lakes, rivers, and reservoirs have important capacity for regulating floods and precipitation. Therefore, river network data can be processed and analyzed to determine its capacity for regulating regional floods and precipitation.

[0027] The areal river network data can be areal vector data of rivers, lakes, reservoirs, etc., stored in shapefile format. The areal river network data can be extracted from remote sensing images based on land cover. The historical water level data is water level sequence data monitored by hydrological stations. The historical water level data is water level data for the area where the hydrological station is located, acquired within a certain time interval; it can be daily water level data or hourly water level data.

[0028] S120: Divide the area river network data and the linear river network data into multiple different river network units, and determine the ring ratio of the different river network units based on the linear river network data.

[0029] In this embodiment, different regions have varying flood control capacities due to differences in river network connectivity, density, and surface area ratio. To accurately estimate the flood control capacity of river networks in different regions, a large area needs to be divided into multiple smaller areas. Specifically, for example, region A is divided into 381 effective river network units of 2.4km x 2.4km. Since lakes have larger surface areas, but their flood control capacity differs from that of rivers, lakes are removed from the river network units for more accurate estimation, resulting in 360 effective river network units.

[0030] S130: Calculate the Hurst index, which characterizes the storage capacity of the area controlled by the hydrological station, based on the historical water level data.

[0031] In this embodiment, the study of the Hurst index (H), based on the rescaled range (R / S) analysis method, originated from British hydrologist Henri Hurst's research on the relationship between water flow and storage capacity in the Nile River reservoir. He discovered that a biased random walk (fractal Brownian motion) could better describe the long-term storage capacity of the reservoir. Based on this, he proposed using the rescaled range (R / S) analysis method to establish the Hurst index as an indicator to determine whether time series data follows a random walk or a biased random walk process. Therefore, the persistence reflected by the Hurst index of the water level series can directly characterize the strength of the river network's regulation capacity. Specifically, for example, a Hurst index greater than 0.5 indicates a strong river network regulation capacity in the region, while a value less than 0.5 indicates a weak one. An increasing Hurst index indicates that the river network's regulation capacity is strengthening or has the potential to strengthen, while a decreasing Hurst index indicates a weakening trend / potential.

[0032] S140: Establish a linear regression model between the Hearst index, which is used to characterize the water storage capacity of the hydrological station, and the river network ratio of the river network unit where the hydrological station is located.

[0033] In this embodiment, after performing correlation analysis on the Hurst index of the area controlled by the hydrological station and factors such as water surface ratio, river network density, hydraulic connectivity, hydraulic circulation, and river network ring ratio in the area controlled by the hydrological station, it was found that the Hurst index and the river network ring ratio in the area controlled by the hydrological station are linearly correlated. That is, the Hurst index can be used to determine the correlation between the Hurst index and the river network ring ratio. arc =a*ψ Nci +b, where Hurst arc The Hearst exponent, ψ, represents the regional water level series. Nci This indicates the ring ratio of the river network in a region, where a and b are constants. Specifically, for example, a linear regression operation is performed between the Hearst index calculated from the water level data of 11 hydrological stations and the ring ratio of the river network in the region where the hydrological station is located, to determine the constants a and b.

[0034] S150: Input the river networks of different river network units in a ring ratio into the linear regression model to obtain the Hurst index, which is used to characterize the water storage capacity of different river network units.

[0035] In this embodiment, hydrological stations are generally located near lakes, reservoirs, and rivers that significantly impact regional water storage capacity. However, small-scale rivers (e.g., those with a width of 10–40 meters) also have a significant impact on regional water storage capacity. Existing technologies primarily evaluate the water storage capacity of small-scale river networks using morphological indicators such as the number and structure of rivers. Therefore, the linear regression model obtained in the above steps can be transferred to the small-scale unit of the river network for calculation, thereby more accurately characterizing the water storage capacity of the river network at a small scale. In this embodiment, the river network unit has a water surface ratio of 5%–12%, and the scale of a single river network unit is 1–10 km. 2 The estimation results of the river network unit's regulation capacity are relatively accurate when the average river width of the river network unit is between 10 and 40 meters. However, for river network units with a water surface ratio below 3%, they are generally insufficient to form a river network. For river network areas or units with a water surface ratio of 3-5%, the peak-shaving efficiency per unit increase in river network area is the strongest, and the water surface ratio should be increased first. River network areas or units with a water surface ratio above 12% can be approximated as lakes, which does not meet the applicable scope of this study.

[0036] In one implementation, determining the ring ratio of different river network units based on the linear river network data may include: obtaining the number of rings and the number of connected river networks for different river network units respectively; and dividing the number of rings by the number of connected river networks to obtain the ring ratio of the river network.

[0037] In this embodiment, the river network loop ratio can be the ratio of the number of looped river networks to the number of effectively connected river networks within a river network unit. Specifically, for example, the number of effectively connected river networks and the number of looped river networks can be calculated using Geographic Information System (GIS) software, and then the river network loop ratio can be obtained.

[0038] In one embodiment, calculating the Hearst index, which characterizes the storage capacity of the area controlled by the hydrological station, based on the historical water level data may include: dividing the historical water level data into multiple historical water level data subsets; calculating the mean of the ratio of the range to the standard deviation of the multiple historical water level data subsets to obtain the Hearst index characterizing the storage capacity of the area controlled by the hydrological station.

[0039] In this embodiment, the Hearst index can be calculated by dividing the daily water level data within a year into 12 hydrological data subsets, where each subset stores one month's water level data records. The standard deviation S of each water level data subset is then calculated. h and range R h Then the Hearst index

[0040] In one embodiment, the historical water level data includes continuous daily water level data from multiple years, and the method may further include: calculating the Hurst index, which characterizes the storage capacity of the area controlled by the hydrological station for multiple years; and averaging the Hurst indices from multiple years to obtain the average Hurst index.

[0041] In this embodiment, to avoid the impact of special events such as rainfall and floods in certain years, the Hearst exponent can be calculated separately for historical water level data over many years, and then the Hearst exponents of these years can be averaged. This can avoid the impact of special circumstances on the linear regression model constructed in the embodiment of this specification.

[0042] In one implementation, drawing linear river network data based on the center of the isometric river network data may include: calculating the average river width of each river in the isometric river network data; if the average river width is greater than or equal to a preset threshold, then extracting the centerline of the river as linear river network data.

[0043] In this embodiment, since there are many narrow rivers in some areas and these rivers have poor connectivity, their ability to regulate floods and rainfall is limited. However, they affect the ring-shaped changes of the river network in the river network unit. Therefore, in order to make the calculation results of small-scale river network units more accurate, only rivers with an average river width of more than 10 meters can be selected for analysis.

[0044] In one embodiment, the method may further include: if the coordinate system of the areal river network data is a geographic coordinate system, then converting the areal river network data into a projected coordinate system.

[0045] In this embodiment, the geographic coordinate system is a spherical coordinate system using latitude and longitude as the map storage unit, while the projected coordinate system is a planar coordinate system whose map unit is meters. To measure the water surface area, length, etc., of the isometric river network data, calculations need to be performed in the projected coordinate system. Therefore, if the isometric river network data is represented using a geographic coordinate system, it needs to be converted to a projected coordinate system beforehand.

[0046] In one embodiment, the method may further include: statistically analyzing the river network density, water surface ratio, number of nodes, and number of river chains of different river network units based on the areal river network data and the linear river network data; calculating the connectivity and circulation degree of different river network units based on the number of nodes and the number of river chains; and analyzing the correlation between the river network density, the water surface ratio, the connectivity, the circulation degree, and the river network regulation and storage capacity.

[0047] In this embodiment, morphological parameters of the river system, such as river network density, water surface ratio, number of nodes, and number of river chains, can be statistically analyzed using area and linear river network data. Then, Pearson correlation coefficient analysis is used to analyze the correlation between river network density, water surface ratio, number of nodes, and number of river chains and the river network's storage capacity. Grey relational analysis can be used to further analyze the differences in the impact of the morphological parameters of each river network unit on the actual storage capacity. Finally, the order of river network optimization and adjustment can be obtained, and the adjustment result is connectivity > river network density > water surface ratio > average width > structural loop connectivity. Therefore, the river network storage capacity can be designed based on this method.

[0048] Please see Figure 2 One embodiment of this application also provides a river network regulation capacity estimation device, which may include: a data acquisition unit, a river network unit division unit, a hydrological station regulation capacity calculation unit, a model construction unit, and a river network regulation capacity estimation unit.

[0049] The data acquisition unit is used to acquire isometric river network data and historical water level data from multiple hydrological stations, and to draw linear river network data based on the center of the isometric river network data.

[0050] The river network unit division unit is used to divide the areal river network data and the linear river network data into multiple different river network units, and to determine the ring ratio of the different river network units based on the linear river network data.

[0051] The hydrological station storage capacity calculation unit is used to calculate the Hurst index, which characterizes the storage capacity of the area controlled by the hydrological station, based on the historical water level data.

[0052] The model building unit is used to establish a linear regression model between the Hearst index, which characterizes the water storage capacity of the hydrological station, and the river network ratio of the river network unit where the hydrological station is located.

[0053] The river network regulation capacity estimation unit is used to input the river network of different river network units into the linear regression model in a ring ratio to obtain the Hearst index, which is used to characterize the regulation capacity of different river network units.

[0054] The specific functions and effects of the river network regulation capacity estimation device can be explained by referring to other embodiments in this specification, and will not be repeated here. Each module in the target identification device can be implemented entirely or partially through software, hardware, or a combination thereof. Each module can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0055] Please see Figure 3 One embodiment of this application also provides an electronic device, which includes a processor and a memory. The memory is used to store a computer program, and when the computer program is executed by the processor, it implements the above-described method for estimating the river network storage capacity.

[0056] The processor can be a central processing unit (CPU). It can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or combinations thereof.

[0057] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the methods in the embodiments of this invention. The processor executes various functional applications and data processing by running the non-transitory software programs, instructions, and modules stored in the memory, thereby implementing the methods described in the above embodiments.

[0058] The memory may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created by the processor, etc. Furthermore, the memory may include high-speed random access memory and non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may optionally include memory remotely located relative to the processor, which can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0059] One embodiment of this application also provides a computer-readable storage medium for storing a computer program that, when executed by a processor, implements the above-described method for estimating river network regulation capacity.

[0060] Those skilled in the art will understand that implementing all or part of the processes in the methods described in this specification can be accomplished by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described. Any references to memory, storage, databases, or other media used in the embodiments provided in this specification can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0061] It should be understood that each block of a flowchart and / or block diagram, and combinations of blocks in a flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing device, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0062] This specification describes various embodiments in a progressive manner. Different embodiments focus on describing the parts that differ from other embodiments. Those skilled in the art, upon reading this specification, will realize that the various embodiments and the technical features disclosed in these embodiments can be combined in numerous ways. For the sake of brevity, not all possible combinations of the technical features in the described embodiments are described. However, any combination of these technical features that does not contradict each other should be considered within the scope of this specification.

[0063] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0064] The various embodiments described in this specification emphasize the parts that differ from other embodiments, and these embodiments can be explained by comparison with each other. Any combination of the various embodiments described in this specification, based on general technical knowledge, is covered within the scope of this specification.

[0065] The above description is merely an embodiment of this invention and is not intended to limit the scope of protection of the claims. Various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principle of this invention should be included within the scope of the claims.

Claims

1. A method for estimating the water storage capacity of a river network, characterized in that, The method includes: Acquire isometric river network data and historical water level data from multiple hydrological stations, and draw linear river network data based on the center of the isometric river network data; The areal river network data and the linear river network data are divided into multiple different river network units, and the ring ratio of the different river network units is determined based on the linear river network data. The Hurst index, used to characterize the storage capacity of the area monitored by the hydrological station, is calculated based on the historical water level data. A linear regression model is established between the Hearst index, which is used to characterize the water storage capacity of the hydrological station, and the river network ratio of the river network unit where the hydrological station is located. By inputting the river networks of different river network units in a ring ratio into the linear regression model, the Hurst index, which is used to characterize the water storage capacity of different river network units, is obtained. Based on the isal river network data and the linear river network data, the river network density, water surface ratio, number of nodes, and number of river chains of different river network units are statistically analyzed. The connectivity and circulation degree of different river network units are calculated based on the number of nodes and the number of river chains. Determining the ring ratio of different river network units based on the linear river network data includes: Obtain the number of looped river networks and the number of connected river networks for different river network units; The number of loops in the river network is divided by the number of connected river networks to obtain the loop ratio of the river network. The Hurst index, used to characterize the water storage capacity of the area controlled by the hydrological station, is calculated based on the historical water level data, including: The historical water level data is divided into multiple subsets of historical water level data. The mean of the ratio of the range to the standard deviation of multiple historical water level data subsets is calculated to obtain the Hearst index, which characterizes the storage capacity of the area controlled by the hydrological station.

2. The method according to claim 1, characterized in that, The historical water level data includes continuous daily water level data from multiple years, and the method further includes: Calculate the Hurst index, which characterizes the storage capacity of the area controlled by the hydrological station, for multiple years. The average Hearst index is obtained by averaging the Hearst indices over multiple years.

3. The method according to claim 1, characterized in that, Drawing linear river network data based on the center of the above-area river network data includes: Calculate the average river width of each river in the isometric river network data; If the average river width is greater than or equal to a preset threshold, the centerline of the river is extracted as linear river network data.

4. The method according to claim 1, characterized in that, The method further includes: If the coordinate system of the isometric river network data is a geographic coordinate system, then the isometric river network data will be converted into a projected coordinate system.

5. The method according to claim 1, characterized in that, The method further includes: The correlation between the river network density, the water surface ratio, the connectivity, the circulation degree, and the river network's regulation and storage capacity was analyzed.

6. A device for estimating the water storage capacity of a river network, characterized in that, The river network regulation and storage capacity estimation device includes: The data acquisition unit is used to acquire isometric river network data and historical water level data from multiple hydrological stations, and to draw linear river network data based on the center of the isometric river network data. The river network unit segmentation unit is used to divide the areal river network data and the linear river network data into multiple different river network units, and to determine the ring ratio of the river network in different river network units based on the linear river network data. Determining the ring ratio of the river network in different river network units based on the linear river network data includes: obtaining the number of rings and the number of connected river networks in each different river network unit; and dividing the number of rings by the number of connected river networks to obtain the ring ratio. The hydrological station's storage capacity calculation unit is used to calculate the Hearst index, which characterizes the storage capacity of the area controlled by the hydrological station, based on the historical water level data. Calculating the Hearst index based on the historical water level data includes: dividing the historical water level data into multiple historical water level data subsets; calculating the mean of the ratio of the range to the standard deviation of the multiple historical water level data subsets to obtain the Hearst index characterizing the storage capacity of the area controlled by the hydrological station. The model building unit is used to establish a linear regression model between the Hearst index, which characterizes the water storage capacity of the hydrological station, and the river network ratio of the river network unit where the hydrological station is located. The river network regulation capacity estimation unit is used to input the river network of different river network units into the linear regression model in a ring ratio to obtain the Hearst index, which is used to characterize the regulation capacity of different river network units. The river network regulation capacity estimation device is also used to calculate the river network density, water surface ratio, number of nodes, and number of river chains of different river network units based on the isal river network data and the linear river network data; and to calculate the connectivity and circulation degree of different river network units based on the number of nodes and the number of river chains.

7. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory being used to store a computer program that, when executed by the processor, implements the method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program that, when executed by a processor, implements the method as described in any one of claims 1 to 5.

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