Water level-reservoir capacity curve construction method and device based on remote sensing image

Abstract

The invention discloses a water level-reservoir capacity curve construction method and device based on a remote sensing image. The method comprises the following steps: collecting basic information of a reservoir, actually measured water level data, characteristic value data and a remote sensing image corresponding to the reservoir; matching a corresponding remote sensing image according to reservoir coordinates and actually measured water level data time, extracting reservoir water surface areas in a wet water period, a dry water period and a flat water period, and fitting the reservoir water surface areas with actually measured water level data to obtain a water level-area relation curve; based on the water level-area relation curve, calculating the dead water level area of the reservoir, and based on the dead water level area and the dead storage capacity, calculating the storage capacities of the reservoir in the wet season, the dry season and the flat season; and fitting to obtain a water level-storage capacity curve based on the storage capacity of the reservoir in the wet season, the dry season and the flat season and the actually measured water level data. According to the method, a new thought is provided for constructing the water level-storage capacity curve of the reservoir without data or with data difficult to obtain.

Description

Technical Field

[0001] The invention relates to the technical field of reservoir characteristic analysis, in particular to a method and device for constructing a water level-reservoir capacity curve based on remote sensing images. Background Art

[0002] The water level-reservoir capacity curve is a function that describes the relationship between the water level and the water storage capacity of a reservoir, and reflects the water storage capacity of a reservoir at different water levels. The water level-reservoir capacity curve is an important tool for reservoir management and dispatching, and is widely used in many fields. In terms of water resources management, the water level-reservoir capacity curve can accurately evaluate the water storage capacity of a reservoir at different water levels, provide a scientific basis for the rational allocation and utilization of water resources, ensure that the water demand for agricultural irrigation, urban water supply, etc. is met in the dry season, and maintain the balance of water supply and demand. In terms of flood control, the water level-reservoir capacity curve helps predict the water storage capacity and flood discharge capacity of the reservoir, provides data support for flood forecasting and early warning, and effectively reduces the flood peak through reasonable dispatching of the reservoir water level, reduces the flood pressure in the downstream area, and reduces the occurrence of flood disasters. In terms of power generation dispatching, the water level-reservoir capacity curve is an important basis for formulating power generation plans, and improves power generation efficiency and economic benefits by optimizing water level regulation. In terms of agricultural irrigation, through accurate water level-reservoir capacity curves, irrigation time and water volume can be reasonably arranged, farmland irrigation efficiency can be improved, and agricultural production can be guaranteed. Therefore, the water level-reservoir capacity curve plays a vital role in reservoir management and scheduling. It is the basis for scientific management and comprehensive utilization of water resources and is of great significance to the management and research of reservoirs.

[0003] The water level-reservoir capacity curve is extremely critical for the management and research of reservoirs. It provides an important scientific basis for the effective use and rational allocation of water resources. However, this type of data is difficult for ordinary users to obtain directly. In addition, the traditional water level-reservoir capacity curve construction method relies more on ground measurement data. This process is not only time-consuming and labor-intensive, but also particularly difficult to implement in some remote or harsh areas. Summary of the invention

[0004] The purpose of the present invention is to provide a method and device for constructing a water level-reservoir capacity curve based on satellite remote sensing images, so that the corresponding water body information of a reservoir without data can be obtained.

[0005] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] In a first aspect, the present invention provides a method for constructing a water level-reservoir capacity curve based on remote sensing images, comprising:

[0007] Collect basic reservoir information, measured water level data, characteristic value data and corresponding remote sensing images of the reservoir;

[0008] According to the reservoir coordinates and the measured water level data time, the corresponding remote sensing image is matched, and the water surface area of ​​the reservoir in the flood season, dry season and normal water season is extracted based on the matched remote sensing image, and the water level-area relationship curve is obtained by fitting with the measured water level data;

[0009] Based on the water level-area relationship curve, the water surface area of ​​the reservoir at dead water level is calculated, and based on the water surface area and dead storage capacity at dead water level, the reservoir capacity in flood season, dry season and normal water season is calculated;

[0010] Based on the reservoir capacity and measured water level data in the flood season, dry season and normal water season, and the corresponding relationship between the reservoir capacity and the water level in the characteristic value data, a water level-reservoir capacity curve is fitted.

[0011] Preferably, the collected basic information of the reservoir includes the name, longitude and latitude of the reservoir;

[0012] The characteristic value data include: dead water level, dead storage capacity, normal high water level, beneficial storage capacity, verified flood level and total storage capacity;

[0013] The processing of the collected remote sensing images corresponding to the reservoir includes: performing radiation calibration and atmospheric correction on the collected remote sensing images corresponding to the reservoir, and obtaining standard framed images and extracting remote sensing image data through RGB combination, uniform light and color, and mosaic cutting.

[0014] Preferably, matching the corresponding remote sensing image according to the reservoir coordinates and the measured water level data time includes:

[0015] According to the coordinates of the reservoir, find the corresponding remote sensing image, and based on the measured water level data time, match the remote sensing image that is closest to the corresponding time of the reservoir.

[0016] Preferably, the extracting of the water surface area of ​​the reservoir in the flood season, dry season and normal water season based on the matched remote sensing image, and fitting with the measured water level data to obtain a water level-area relationship curve includes:

[0017] Extracting the boundary file of the reservoir water surface area from the matched remote sensing image to calculate and obtain the reservoir water surface area in the flood season, dry season and normal water season;

[0018] Based on the extracted reservoir water surface area data and the corresponding measured water level data, a logarithmic or exponential relationship is used to fit the water level-area curve.

[0019] Preferably, the method further comprises:

[0020] Using R 2 Determine the fitting of the water level-area curve and select the curve with the best fitting effect as the water level-area curve.

[0021] Preferably, the calculating of the water surface area at the dead water level of the reservoir based on the water level-area relationship curve, and the calculating of the reservoir capacity in the flood season, dry season and normal water season based on the water surface area and dead storage capacity at the dead water level, comprises:

[0022] Substituting the dead water level in the collected characteristic value data into the water level-area relationship curve to calculate the water surface area of ​​the reservoir at the dead water level;

[0023] The water levels in the flood season, dry season and normal water season are sorted in ascending order, and are defined as the first moment water level, the second moment water level and the third moment water level respectively, and the corresponding areas are the first moment area, the second moment area and the third moment area;

[0024] Based on the dead storage capacity in the characteristic value data, the area at the first moment, the area at the second moment and the reservoir capacity at the third moment are calculated by cumulative addition using the prism method, as follows:

[0025] ,

[0026] in, is the change in reservoir capacity, For the Water level at all times, For the The water surface area of ​​the reservoir at that moment, is the dead water level of the reservoir, is the dead water area;

[0027] Computational-based , the storage capacity at the first moment is the dead storage capacity plus the storage capacity change , the storage capacity at the second moment is the storage capacity at the first moment plus the storage capacity change , the storage capacity at the third moment is the storage capacity at the second moment plus the storage capacity change , and finally calculate the reservoir capacity during the flood season, dry season and normal water season.

[0028] Preferably, the correspondence between the reservoir capacity and the water level in the characteristic value data is: the verified flood level corresponds to the total reservoir capacity, the normal high water level corresponds to the sum of the beneficial reservoir capacity and the dead reservoir capacity, and the dead water level corresponds to the dead reservoir capacity.

[0029] Preferably, the water level-reservoir capacity curve is obtained by fitting based on the reservoir capacity and measured water level data in the flood season, dry season and normal water season, and the corresponding relationship between the reservoir capacity and the water level in the characteristic value data, including:

[0030] The total storage capacity in the characteristic value data and the verified flood level form a group of data, the beneficial storage capacity and the dead storage capacity are added together with the normal high water level to form a group of data, the dead storage capacity and the dead water level form a group of data, the calculated flood season storage capacity and water level form a group of data, the dry season storage capacity and water level form a group of data, and the normal water season storage capacity and water level form a group of data; the 6 groups of data are respectively substituted into the water level-storage capacity fitting relationship to obtain fitting parameters, and finally the water level-storage capacity curve is obtained;

[0031] The water level-storage capacity fitting relationship is:

[0032] ,

[0033] in, is the dead water level of the reservoir, It is the dead storage capacity of the reservoir. , are fitting parameters, is the water level, For storage capacity.

[0034] In a second aspect, the present invention provides a water level-reservoir capacity curve construction device based on remote sensing images, which is used to implement the above-mentioned water level-reservoir capacity curve construction method based on remote sensing images, and the device comprises:

[0035] Data collection module, used to collect basic reservoir information, measured water level data, characteristic value data and corresponding remote sensing images of the reservoir;

[0036] The first fitting module is used to match the corresponding remote sensing image according to the reservoir coordinates and the measured water level data time, extract the reservoir water surface area in the flood season, dry season and normal water season based on the matched remote sensing image, and fit it with the measured water level data to obtain a water level-area relationship curve;

[0037] A calculation module, for calculating the water surface area of ​​the reservoir at dead water level based on the water level-area relationship curve, and calculating the reservoir capacity in flood season, dry season and normal water season based on the water surface area and dead storage capacity at dead water level;

[0038] The second fitting module is used to fit the water level-reservoir capacity curve based on the reservoir capacity and measured water level data in the flood season, dry season and normal water season, and the corresponding relationship between the reservoir capacity and the water level in the characteristic value data.

[0039] The invention provides a method for constructing a water level-reservoir capacity curve based on remote sensing images, which has the following beneficial effects:

[0040] Based on reservoir information and remote sensing image processing, the present invention extracts the water surface area at different times, matches it with the water level data at the corresponding time, fits the water level-area curve, and calculates the water surface area at the dead water level. The prism method is used to calculate the reservoir capacity at different times by accumulation, and matches it with the water level data at the corresponding time, and finally fits the water level-capacity relationship curve together with the collected characteristic value data, which provides a new idea for the construction of the water level-capacity curve for reservoirs with no data or difficult to obtain data. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A flow chart of a method for constructing a water level-reservoir capacity curve based on remote sensing images provided in an embodiment of the present invention;

[0042] Figure 2 This is a diagram showing the extraction results of the water surface area of ​​Yubei Reservoir during the flood season, dry season and normal water season in the embodiment of the present invention;

[0043] Figure 3 It is a schematic diagram of the fitting result of the water level-area curve of Yubei Reservoir in an embodiment of the present invention;

[0044] Figure 4 It is a schematic diagram of the fitting results of the water level-reservoir capacity curve of Yubei Reservoir in an embodiment of the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments and the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0046] It should also be noted that, in order to avoid obscuring the present invention due to unnecessary details, only structures and / or processing steps closely related to the solutions according to the present invention are shown in the accompanying drawings, while other details that are not closely related to the present invention are omitted.

[0047] It should be emphasized that the term “include / comprises” when used herein refers to the presence of features, elements, steps or components, but does not exclude the presence or addition of one or more other features, elements, steps or components.

[0048] It should be emphasized here that the step marks mentioned below are not intended to limit the order of the steps, but it should be understood that the steps can be executed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be executed simultaneously.

[0049] The present invention extracts the water surface area at different times based on the collected reservoir water level information and remote sensing images, matches it with the water level data at the corresponding time, fits the water level-area curve, and calculates the water surface area at the dead water level. The prism method is used to calculate the reservoir capacity at different times by accumulation, and matches it with the water level data at the corresponding time, and finally fits the water level-capacity relationship curve together with the collected characteristic value data.

[0050] Based on the above invention concept, an embodiment of the present invention provides a method for constructing a water level-reservoir capacity curve based on remote sensing images, see Figure 1 , the method comprising:

[0051] S1: Collect basic reservoir information, measured water level data, characteristic value data and corresponding remote sensing images of the reservoir;

[0052] S2: According to the reservoir coordinates and the measured water level data time, the corresponding remote sensing images are matched to extract the reservoir water surface area during the flood, dry and normal water seasons, and then matched with the measured water level data to fit the water level-area relationship curve;

[0053] S3: Based on the constructed water level-area relationship curve, the water surface area when the reservoir is at dead water level is calculated. The prism method is used based on the dead storage capacity to calculate the reservoir capacity in the flood, dry and normal water periods by accumulation.

[0054] S4: Construct a water level-reservoir capacity curve based on the reservoir capacity and measured water level data during the flood, dry and normal water seasons.

[0055] In the embodiment of the present invention, the specific implementation process of step S1 is as follows:

[0056] S11: Collect basic information and characteristic value data of the reservoir, where the basic information includes the name, longitude and latitude of the reservoir; the characteristic value data includes dead water level, dead storage capacity, normal high water level, beneficial storage capacity, verified flood level and total storage capacity;

[0057] S12: Perform radiometric calibration and atmospheric correction on the collected remote sensing images corresponding to the reservoir, and obtain standard framing image products and extract remote sensing image data through image processing such as RGB combination, uniform light and color, and mosaic cropping.

[0058] In the embodiment of the present invention, the specific implementation process of step S2 is as follows:

[0059] S21: According to the reservoir coordinates, find the corresponding remote sensing image, and match the corresponding time of the reservoir or the remote sensing image closest to that time based on the measured water level data time; it should be noted that the reservoir coordinates are known data, and there are many ways to obtain them, such as searching online or going to relevant departments; since the remote sensing image contains coordinate information, the longitude and latitude can be used to determine the location of the reservoir;

[0060] S22: Use geographic information software to calculate the extracted reservoir water surface area boundary file, and finally obtain the reservoir water surface area in the flood season, dry season, and normal water season; Figure 2 As shown, the water surface area of ​​the reservoir in flood season, dry season and normal water season was obtained based on the remote sensing image extraction of Yubei Reservoir;

[0061] S23: Based on the extracted reservoir water surface area data and the corresponding measured water level data, a water level-area curve is fitted using a logarithmic or exponential relationship.

[0062] In this embodiment, according to the remote sensing image time at three moments, the measured water level data closest to the remote sensing image time is found to match the reservoir water surface area and water level data at three moments. The water level-area curve is fitted using a logarithmic or exponential relationship, and the logarithmic and exponential relationship formulas are:

[0063] ,

[0064] ,

[0065] Where: , , All are parameters; water level is the independent variable, area As the dependent variable, the water level-area curve fitting results are as follows Figure 3 shown.

[0066] Furthermore, R 2 To judge the curve fitting situation, and select the curve with the best fitting effect as the water level-area curve, R 2 The calculation formula is:

[0067] ,

[0068] Where: is the measured value, is the analog value, It is the measured average value.

[0069] In the embodiment of the present invention, the specific implementation process of step S3 is as follows:

[0070] S31: Based on the dead water level data in the reservoir characteristic value, substitute it into the constructed water level-area relationship curve to calculate the water surface area at the dead water level of the reservoir;

[0071] S32: Based on the dead storage capacity data in the reservoir characteristic value, the reservoir capacity in the flood season, dry season and normal water season is calculated by cumulative method using the prism method;

[0072] The water levels in the flood season, dry season, and normal water season are arranged in ascending order, namely the first moment water level, the second moment water level, and the third moment water level. The corresponding areas are the first moment area, the second moment area, and the third moment area. The calculation formula of the prism method is:

[0073] ,

[0074] Where: For the Water level at the moment, m; For the Reservoir surface area at the moment, m 2 ; is the change in reservoir capacity, m 3 ; is the dead water level of the reservoir, m; is the dead water area, m 2 .

[0075] The storage capacity at the first moment is the dead storage capacity plus the first storage capacity change , the storage capacity at the second moment is the storage capacity at the first moment plus the change in the second storage capacity The storage capacity at the third moment is the storage capacity at the second moment plus the change in storage capacity at the third moment. , and finally the reservoir capacity at three moments is calculated.

[0076] In the embodiment of the present invention, the specific implementation process of step S4 is as follows:

[0077] S41: According to the corresponding relationship between the reservoir characteristic values, i.e., the correspondence between the check flood level and the total storage capacity, the correspondence between the normal high water level and the sum of the beneficial storage capacity and the dead storage capacity, and the correspondence between the dead water level and the dead storage capacity, find the corresponding three sets of data;

[0078] S42: According to the three sets of data corresponding to the reservoir characteristic values ​​and the reservoir capacity in the flood season, dry season and normal water season calculated based on remote sensing images and the corresponding measured water level data, the water level-reservoir capacity curve is fitted. The fitting relationship is:

[0079] ,

[0080] Where: is the dead water level of the reservoir, m; is the dead storage capacity of the reservoir, m 3 ; , All parameters, water level is the independent variable, storage capacity is the dependent variable,

[0081] The total storage capacity and the verified flood level form a set of data, the beneficial storage capacity and the dead storage capacity are added together with the normal high water level to form a set of data, and the dead storage capacity and the dead water level form a set of data; the calculated flood season storage capacity and water level form a set of data, the dry season storage capacity and water level form a set of data, and the normal water season storage capacity and water level form a set of data. Substitute the 6 sets of data into the above fitting formula respectively, and the fitting parameters , , and the water level-storage capacity curve of the reservoir is obtained. The curve fitting results are as follows Figure 4 As shown, the black points are reservoir characteristic value data, and the red points are water level and reservoir capacity data extracted based on remote sensing images.

[0082] The present embodiment provides a method for constructing a water level-reservoir capacity curve based on remote sensing images. The method extracts the water surface area at different times based on the basic information of the reservoir and the processing of remote sensing images, matches the water level data at the corresponding times, fits the water level-area curve, and further calculates the water surface area at the dead water level. The prism method is used to calculate the reservoir capacity at different times by accumulation, matches the water level data at the corresponding times, and finally fits the water level-reservoir capacity relationship curve, which provides a new idea for constructing the water level-reservoir capacity curve for reservoirs with no data or data that is difficult to obtain.

[0083] Based on the above inventive concept, the present invention also provides a water level-reservoir capacity curve construction device based on remote sensing images, which is used to implement the above water level-reservoir capacity curve construction method based on remote sensing images, and the device includes:

[0084] Data collection module, used to collect basic reservoir information, measured water level data, characteristic value data and corresponding remote sensing images of the reservoir;

[0085] The first fitting module is used to match the corresponding remote sensing image according to the reservoir coordinates and the measured water level data time, extract the reservoir water surface area in the flood season, dry season and normal water season based on the matched remote sensing image, and fit it with the measured water level data to obtain a water level-area relationship curve;

[0086] A calculation module, used to calculate the dead water level area of ​​the reservoir based on the water level-area relationship curve, and to calculate the reservoir capacity in the flood season, dry season and normal water season based on the dead water level area and dead storage capacity;

[0087] The second fitting module is used to fit the water level-reservoir capacity curve based on the reservoir capacity and measured water level data in the flood season, dry season and normal water season, and the corresponding relationship between the reservoir capacity and the water level in the characteristic value data.

[0088] It is worth pointing out that the device embodiment corresponds to the above-mentioned method embodiment, and the implementation methods of the above-mentioned method embodiments are all applicable to the device embodiment and can achieve the same or similar technical effects, so they will not be repeated here.

[0089] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0090] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the 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, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0091] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0092] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0093] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for constructing a water level-reservoir capacity curve based on remote sensing images, characterized in that: include: Collect basic reservoir information, measured water level data, characteristic value data and corresponding remote sensing images of the reservoir; According to the reservoir coordinates and the measured water level data time, the corresponding remote sensing image is matched, and the water surface area of ​​the reservoir in the flood season, dry season and normal water season is extracted based on the matched remote sensing image, and the water level-area relationship curve is obtained by fitting with the measured water level data; Based on the water level-area relationship curve, the water surface area of ​​the reservoir at dead water level is calculated, and based on the water surface area and dead storage capacity at dead water level, the reservoir capacity in flood season, dry season and normal water season is calculated; Based on the reservoir capacity and measured water level data in the flood season, dry season and normal water season, and the corresponding relationship between the reservoir capacity and the water level in the characteristic value data, a water level-reservoir capacity curve is fitted.

2. The method for constructing a water level-reservoir capacity curve based on remote sensing images according to claim 1, characterized in that: The collected basic reservoir information includes the reservoir name, longitude and latitude; The characteristic value data include: dead water level, dead storage capacity, normal high water level, beneficial storage capacity, verified flood level and total storage capacity; The processing of the collected remote sensing images corresponding to the reservoir includes: performing radiation calibration and atmospheric correction on the collected remote sensing images corresponding to the reservoir, and obtaining standard framed images and extracting remote sensing image data through RGB combination, uniform light and color, and mosaic cutting.

3. The method for constructing a water level-reservoir capacity curve based on remote sensing images according to claim 2, characterized in that: The method of matching the corresponding remote sensing image according to the reservoir coordinates and the measured water level data time includes: According to the coordinates of the reservoir, find the corresponding remote sensing image, and based on the measured water level data time, match the remote sensing image that is closest to the corresponding time of the reservoir.

4. The method for constructing a water level-reservoir capacity curve based on remote sensing images according to claim 3, characterized in that: The water surface area of ​​the reservoir in the flood season, dry season and normal water season is extracted based on the matched remote sensing image, and is fitted with the measured water level data to obtain a water level-area relationship curve, including: Extract the boundary file of reservoir water surface area from the matched remote sensing images and calculate the reservoir water surface area in flood season, dry season and normal water season; Based on the extracted reservoir water surface area data and the corresponding measured water level data, a logarithmic or exponential relationship is used to fit the water level-area curve.

5. The method for constructing a water level-reservoir capacity curve based on remote sensing images according to claim 4, characterized in that: The method further comprises: Using R 2 Determine the fitting of the water level-area curve and select the curve with the best fitting effect as the water level-area curve.

6. The method for constructing a water level-reservoir capacity curve based on remote sensing images according to claim 5, characterized in that: The method of calculating the water surface area of ​​the reservoir at the dead water level based on the water level-area relationship curve, and calculating the reservoir capacity in the flood season, dry season and normal water season based on the water surface area and dead storage capacity at the dead water level, includes: Substituting the dead water level in the collected characteristic value data into the water level-area relationship curve to calculate the water surface area of ​​the reservoir at the dead water level; The water levels in the flood season, dry season and normal water season are sorted in ascending order, and are defined as the first moment water level, the second moment water level and the third moment water level respectively, and the corresponding areas are the first moment area, the second moment area and the third moment area; Based on the dead storage capacity in the characteristic value data, the prism method is used to calculate the reservoir capacity at the first moment, the second moment and the third moment by accumulation, and the calculation is as follows: ， in, is the change in reservoir capacity, For the Water level at all times, For the The water surface area of ​​the reservoir at that moment, is the dead water level of the reservoir, is the dead water area; Computational-based , the storage capacity at the first moment is the dead storage capacity plus the storage capacity change , the storage capacity at the second moment is the storage capacity at the first moment plus the storage capacity change , the storage capacity at the third moment is the storage capacity at the second moment plus the storage capacity change , and finally calculate the reservoir capacity during the flood season, dry season and normal water season.

7. The method for constructing a water level-reservoir capacity curve based on remote sensing images according to claim 6, characterized in that: The corresponding relationship between the reservoir capacity and the water level in the characteristic value data is: the verified flood level corresponds to the total reservoir capacity, the normal high water level corresponds to the sum of the beneficial reservoir capacity and the dead reservoir capacity, and the dead water level corresponds to the dead reservoir capacity.

8. The method for constructing a water level-reservoir capacity curve based on remote sensing images according to claim 7, characterized in that: The water level-reservoir capacity curve is obtained by fitting based on the reservoir capacity and measured water level data in the flood season, dry season and normal water season, and the corresponding relationship between the reservoir capacity and the water level in the characteristic value data, including: The total storage capacity in the characteristic value data and the verified flood level form a group of data, the beneficial storage capacity and the dead storage capacity are added together with the normal high water level to form a group of data, the dead storage capacity and the dead water level form a group of data, the calculated flood season storage capacity and water level form a group of data, the dry season storage capacity and water level form a group of data, and the normal water season storage capacity and water level form a group of data; the 6 groups of data are respectively substituted into the water level-storage capacity fitting relationship to obtain fitting parameters, and finally the water level-storage capacity curve is obtained; The water level-storage capacity fitting relationship is: ， in, is the dead water level of the reservoir, It is the dead storage capacity of the reservoir. , are fitting parameters, is the water level, For storage capacity.

9. A device for constructing a water level-reservoir capacity curve based on remote sensing images, characterized in that: The device is used to implement the method for constructing a water level-reservoir capacity curve based on remote sensing images as described in any one of claims 1 to 8, and comprises: Data collection module, used to collect basic reservoir information, measured water level data, characteristic value data and corresponding remote sensing images of the reservoir; The first fitting module is used to match the corresponding remote sensing image according to the reservoir coordinates and the measured water level data time, extract the reservoir water surface area in the flood season, dry season and normal water season based on the matched remote sensing image, and fit it with the measured water level data to obtain a water level-area relationship curve; A calculation module, for calculating the water surface area of ​​the reservoir at dead water level based on the water level-area relationship curve, and calculating the reservoir capacity in flood season, dry season and normal water season based on the water surface area and dead storage capacity at dead water level; The second fitting module is used to fit the water level-reservoir capacity curve based on the reservoir capacity and measured water level data in the flood season, dry season and normal water season, and the corresponding relationship between the reservoir capacity and the water level in the characteristic value data.

Images