A method, a computing device, and a storage medium for calculating the average water level of a lake

Abstract

The present invention discloses a method, a computing device and a storage medium for calculating the average water level of a lake. The method includes obtaining underwater DEM data of the lake area and measured water level data of water level stations in the lake area, and using each grid unit of the DEM as a calculation unit; obtaining the locations of each water level station and the flood control project control range, and deriving the empirical average water level of the lake area; based on the underwater DEM data, obtaining the static storage capacity of the lake at different water levels, and deriving the water level-storage capacity relationship curve based on the lake bottom topography; according to the measured water level data of the water level stations and the underwater DEM data, deriving the dynamic storage capacity of the lake at each moment during the flood period; using the method for calculating the average water level of the lake considering the dynamic storage capacity of the lake during the flood period to calculate the average water level; the device includes a processor and a memory; and a program or instruction is stored on the storage medium. The present invention provides a calculation method, a computing device and a storage medium that can improve the accuracy of calculating the average water level of the lake according to the water level-storage capacity relationship curve, and reduce the risk of flood control scheduling decisions.

Description

Technical Field

[0001] The present invention relates to the field of flood forecasting, and particularly to a method for calculating the average water level of a lake, a calculating device and a storage medium. Background Art

[0002] Flood forecasting and scheduling are important non-engineering measures for lake and reservoir management and flood control and disaster reduction. Accurately calculating the average water level of a lake during the flood period is the main basis for scientifically scheduling water conservancy projects. In the prior art, the most commonly used method for calculating the average water level of a lake is the static storage capacity method, that is, the average water level of the lake is deduced according to the water level-storage capacity relationship curve surveyed during the design and construction of the lake and reservoir. By calculating the total water storage of the lake at each moment and querying the corresponding average water level, it is possible to more accurately and real-time consider the changes in the water level of the lake area, and it has good determination ability and application prospects in theory, and is widely used in flood forecasting and scheduling of lake areas in various regions. However, during the flood period, affected by the flood discharge of the sluice, the water level of the lake area fluctuates, and the representativeness of the water level station is reduced. When using the water level-storage capacity relationship curve, it is necessary to have data on the inflow of the lake area and the water inflow into the lake during the time period, which cannot meet the calculation of the average water level for lake areas lacking data. Moreover, after the lake and reservoir have been operating for a certain period of time, the topographic and geomorphic features of the reservoir area have changed due to geological phenomena such as sediment deposition and bank collapse, resulting in a large difference between the actual water level-storage capacity and water level-area relationships and those before the reservoir was built, affecting the calculation accuracy and application effect of deducing the average water level of the lake using the water level-storage capacity relationship curve. Summary of the Invention

[0003] Object of the Invention: The object of the present invention is to provide a method for calculating the average water level of a lake, a calculating device and a storage medium that can improve the accuracy of calculating the average water level of a lake according to the water level-storage capacity relationship curve and reduce the risk of flood control scheduling decisions.

[0004] Technical Solution: To achieve the above object, a method for calculating the average water level of a lake according to the present invention includes the following steps:

[0005] Step S1, obtain the underwater DEM (Digital Elevation Model) data of the lake area and the measured water level data of the water level stations in the lake area, and use each grid unit of the DEM as a calculation unit;

[0006] Step S2, combine the engineering design data such as the distribution of flood control projects and the opening of the gates in the lake area, obtain the locations of each water level station and the flood control project control range, and deduce the empirical average water level of the lake area;

[0007] Step S3, based on the underwater DEM data, obtain the static storage capacity of the lake under different water level conditions in the lake area, and deduce the water level-storage capacity relationship curve based on the current lake bottom topography;

[0008] Step S4: Calculate the water level of each grid cell in the lake area based on the measured water level data of the water level station and the underwater DEM data, and derive the dynamic storage capacity of the lake at each moment during the flood period;

[0009] Step S5: Calculate the average water level using the lake average water level calculation method considering the dynamic storage capacity of the lake during the flood period.

[0010] The calculation method of the empirical average water level of the lake area described in Step S2 is as follows:

[0011]

[0012] Where, is the empirical average water level of the lake area obtained according to the empirical weight coefficient, with the unit of m, k j is the empirical weight coefficient, which is determined by the location of the water level station and the flood control project control range, Z j is the measured water level of each water level station.

[0013] The calculation method of the static storage capacity of the lake under different water level conditions described in Step S3 is as follows:

[0014]

[0015] Where, V z is the static storage capacity of the lake under different water level conditions, with the unit of m, V p，TIN is the storage capacity calculated by generating TIN by ARCGIS (GIS platform) under different water level conditions, with the unit of m 3 , Z q is the different water levels input in GIS (Geographic Information System), with the unit of m, m is the number of TINs, and TIN is an irregular triangular network.

[0016] The derivation of the dynamic storage capacity V of the lake at each moment during the flood period described in Step S4 t is solved by the following formula:

[0017]

[0018] Where, V t is the dynamic storage capacity of the lake at a certain moment, with the unit of m 3 , Z i，t is the water depth of a grid cell in the lake area at a certain moment, with the unit of m, which is equal to the water level of the i-th grid cell in the underwater DEM data minus its lake bottom elevation, i is the number of calculation units in the lake area, and R is the spatial resolution of the calculation unit, which is 5m.

[0019] The calculation method of the water level of each watershed grid cell is as follows:

[0020]

[0021] In the formula, Z i is the water level of each grid cell, with the unit of m, and Z j is the measured water level of the water level station in the lake area, with the unit of m, n represents the number of water level stations, and λ i，j is the distance weight from any grid cell in the lake area to a certain water level station.

[0022] The distance weight from any grid cell in the lake area to a certain water level station is obtained by solving the following formula:

[0023]

[0024] In the formula, the distance weight λ i，j is a function of the reciprocal of the distance, and d i，j is the distance from any grid cell in the lake area to a certain water level station, with the unit of m.

[0025] The method for calculating the average water level of the lake considering the dynamic storage capacity of the lake during the flood period in step S5 is as follows:

[0026]

[0027] In the formula, is the average water level of the lake at a certain moment, with the unit of m, V t is the dynamic storage capacity of the lake at a certain moment, with the unit of m 3 , f is a function determined by the water level-static storage capacity relationship curve measured by ARCGIS. By inputting different water level values into the GIS in combination with the DEM of the lake area, the new water level-storage capacity relationship curve of the lake area is obtained, considering the influence of natural effects and human activities on the landform of the lake area.

[0028] A device for calculating the average water level of a lake includes a processor and a memory; the memory stores a program or instruction, and the program or instruction is loaded and executed by the processor to implement the steps of the method for calculating the average water level of the lake according to any one of claims 1 to 7.

[0029] A computer-readable storage medium stores a program or instruction thereon, and the program or instruction, when executed by a processor, implements the steps of the method for calculating the average water level of the lake according to any one of claims 1 to 7.

[0030] Beneficial effects: The present invention has the following remarkable advantages: The present invention proposes a method for calculating the average water level of grid cells based on the dynamic storage capacity of the lake, considering the influence of the operation of floodgates during the flood period on the calculation of the average water level of the lake, solves the problem that the existing static storage capacity method cannot well reflect the water surface fluctuation of the lake during the flood period when floodgates are operating, can effectively improve the accuracy of calculating the average water level of the lake according to the water level-storage capacity relationship curve, and reduce the risk of flood control scheduling decisions. Brief Description of the Drawings

[0031] Figure 1 is a schematic flow chart of the method for calculating the average lake level considering the operation of the sluice during the flood period in the water level - storage capacity relationship curve method provided by the present invention;

[0032] Figure 2 is the spatial distribution of water level stations in the basin and the flood control project control scope in the specific embodiment;

[0033] Figure 3 is a comparison chart of the water level - storage capacity relationship curve considering the operation of the sluice during the flood period and the water level - storage capacity curve before the reservoir construction in the basin in the specific embodiment;

[0034] Figure 4 is the distribution map of the dynamic storage capacity of the lake for each grid in the basin in the specific embodiment;

[0035] Figure 5 is the calculation result of the average lake level considering the operation of the sluice during the flood period in the basin in the specific embodiment. Detailed Embodiment

[0036] The technical solution of the present invention will be described in detail below in conjunction with the embodiments and the drawings.

[0037] As Figure 1 shown, the present invention provides a method for calculating the average lake level considering the operation of the sluice during the flood period at the grid scale based on mathematical and physical methods, including the following steps:

[0038] Step S1: Obtain the underwater DEM data of the lake area and the measured water level data of the water level stations in the lake area, and use each grid cell of the DEM as the calculation unit, which specifically includes the following sub - steps:

[0039] Step S101: Obtain the underwater DEM data of the lake area and the measured water level data of the water level stations in the lake area;

[0040] Step S102: Use each grid cell of the DEM as the calculation unit:

[0041]

[0042] In the formula, LC i is the i - th grid calculation unit in the lake area, R is the side length of the calculation unit, SR is the spatial resolution of the underwater DEM, NaN represents not a calculation unit, and 1 represents a calculation unit.

[0043] Obtain the underwater DEM data of the upper lake in the Nansi Lake Basin and the measured water level data of the water level stations in the lake area, and use each grid cell of the DEM as the calculation unit.

[0044] Step S2: Combine the engineering design data such as the distribution of flood control projects and the opening of gates in the lake area, collect the information of the water resources census, obtain the locations of each water level station and the control scope of flood control projects, and derive the empirical average water level of the lake area. Specifically, it includes the following sub-steps:

[0045] Step S201: Combine the engineering design data such as the distribution of flood control projects and the opening of gates in the lake area, collect the information of the water resources census, obtain the locations of each water level station, and obtain the control scope of flood control projects through steps such as capturing pour points and watersheds in the GIS spatial analysis tool;

[0046] Step S202: Determine the representative water level stations in the lake area and the corresponding empirical weight coefficients of each water level station according to the information of the water resources census, the forecasting experience of the water conservancy department, and the control scope of flood control projects:

[0047]

[0048] In the formula, k j is the empirical weight coefficient, which is determined by the location of the water level station and the control scope of flood control projects, data wl = 1 indicates that there is a specification for calculating the empirical average water level of the lake in this lake area, k jwl i.e., the weight of each water level station in the specification, n is the number of water level stations, data wl = 0 indicates that there is no specification for calculating the empirical average water level of the lake in this lake area.

[0049] Step S203: Derive the empirical average water level of the lake area according to the empirical weight coefficient:

[0050]

[0051] In the formula, is the empirical average water level of the lake area obtained according to the empirical weight coefficient, with the unit of m, Z j is the measured water level of each water level station, with the unit of m.

[0052] Analyze the engineering design data such as the distribution of flood control projects and the opening of gates in the upper lake area, and collect the information of the water resources census to obtain the locations of each water level station and the control scope of flood control projects, as Figure 2 shown; calculate the empirical weight coefficients of each water level station and derive the empirical average water level of the lake area.

[0053] Step S3: Based on the underwater DEM data, use geographic information software to obtain the lake storage capacity under different water level conditions in the lake area, and derive the water level-storage capacity relationship curve based on the current lake bottom topography. Specifically, it includes the following sub-steps:

[0054] Step S301: Based on the underwater DEM data, use geographic information software to obtain the static lake storage capacity under different water level conditions in the lake area:

[0055]

[0056] Wherein, V z is the static storage capacity of the lake under different water level conditions, with the unit of m, and V p，TIN is the storage capacity calculated by generating TIN by ARCGIS under different water level conditions, with the unit of m 3 , Z q are different water levels input in GIS, with the unit of m, m is the number of TINs, and TIN is an irregular triangular network;

[0057] Step S302, derive the water level-storage capacity relationship curve based on the current lake bottom topography:

[0058] Z q = f(V z ) (5)

[0059] Wherein, f is the water level-storage capacity relationship function based on the current lake bottom topography determined by GIS by measuring the underwater DEM of the lake area.

[0060] Analyze the underwater DEM data of the upper-level lake, obtain the lake storage capacity of the lake area under different water level conditions, and derive the water level-storage capacity relationship curve based on the current lake bottom topography, as Figure 3 shown.

[0061] Step S4, according to the measured water level data of the water level station and the underwater DEM data, calculate the water level of each grid cell in the lake area, and derive the dynamic storage capacity of the lake at each moment during the flood period, specifically including the following sub-steps:

[0062] Step S401, according to the measured water level data of the water level station and the underwater DEM data, calculate the weight of each water level station for each grid cell in the lake area:

[0063]

[0064] Wherein, the distance weight λ i，j is a function of the reciprocal of the distance, and d i，j is the distance from any grid cell in the lake area to a certain water level station, with the unit of m.

[0065]

[0066] Wherein, (x j , y j ) are the position coordinates of a certain water level station in the lake area, and (x j , y j ) are the position coordinates of any point in the lake area.

[0067] Step S402, according to the weight of each water level station for each grid cell, calculate the water level of each grid cell in the lake area:

[0068]

[0069] Wherein, Z i is the water level of each grid cell, in m, Z j is the measured water level of the water level station in the lake area, in m, n represents the number of water level stations, and λ i，j is the distance weight from any grid cell in the lake area to a certain water level station.

[0070] Step S403: Considering the influence of the inflow of tributaries into the lake and the flood discharge of the sluice, divide the underlying surface of the lake area by calculation units, and use the idea of integration to deduce the dynamic storage capacity of the lake at each moment during the flood period:

[0071]

[0072] Wherein, V t is the dynamic storage capacity of the lake at a certain moment, in m 3 , Z i，t is the water depth of a certain grid cell in the lake area at a certain moment, in m, which is equal to the water level of the i-th grid cell in the underwater DEM data minus its lake bottom elevation, i is the number of calculation units in the lake area, and R is the spatial resolution of the calculation unit, which is 5 m.

[0073] According to the measured water level data of Houying, Nanyang, Makou, and under the No. 1 sluice in the upper lake area and combined with the underwater DEM data, calculate the distance weight and water level of the four water level stations in each grid cell in the lake area, and deduce the dynamic storage capacity of the lake at each moment during the flood period, as Figure 4 shown.

[0074] Step S5: Construct a calculation method for the average water level of the lake considering the dynamic storage capacity of the lake during the flood period, specifically including the following sub-steps:

[0075] Step S501: Query the corrected lake water level-capacity curve based on the current lake bottom situation, take the dynamic storage capacity of the lake as the dynamic water storage volume of the lake, and obtain the corresponding average water level that can reflect the dynamic fluctuation of the lake surface:

[0076]

[0077] Wherein, is the average water level of the lake at a certain moment, in m, V t is the dynamic storage capacity of the lake at a certain moment, in m 3 , and f is the water level-capacity relationship function based on the current lake bottom topography determined by GIS by measuring the underwater DEM of the lake area, considering the influence of natural actions and human activities on the landform of the lake area.

[0078] Step S502: Select the measured water level data of 4 water level stations in the upper lake, calculate the average lake water level considering the dynamic storage capacity of the lake and the average water level corresponding to the empirical weight method respectively, and select two indicators: the water level difference (the difference between the average water level obtained by the dynamic storage capacity integration method and the water level obtained by the empirical weight method) and the correlation coefficient (reflecting the linear correlation degree between the average water level and the water level of the representative station in the lake area). The calculation formulas are as follows:

[0079]

[0080]

[0081] In the formula, Δ is the water level difference, with the unit of m, is the average water level obtained by the dynamic storage capacity integration method, with the unit of m, is the average water level obtained by the empirical weight method, with the unit of m, is the water level of the representative station in the lake area, with the unit of m, r is the correlation coefficient. The greater the correlation coefficient between the average water level and the water level of the representative station, the higher the representativeness of the average lake water level calculated by this method. Ave is the average value of a set of water level data.

[0082] Calculate the water level difference and the correlation coefficient, and determine that the method with a stable and concentrated water level difference and a larger correlation coefficient can reflect the average water level calculation method of the actual storage capacity of the lake. Finally, obtain the calculation result of the average lake water level and the comparison with the water level of the representative station Nanyang, as Figure 5 shown. The method for calculating the average lake water level considering the operation of the sluice during the flood period corrects the water level - storage capacity relationship curve of the lake area and then calculates the dynamic storage capacity of the lake to derive the average lake water level. This method enables the calculated average lake water level to more accurately and real - time reflect the dynamic changes of the lake water storage volume and reduces the flood control decision - making risk. After considering the operation of the sluice during the flood period, the data with the water level difference falling within the range of 5.0 - 8.0 cm accounts for 85.3% of the total, and the correlation coefficient is increased from 0.978 to 0.987.

[0083] This embodiment provides a device for calculating the average lake water level, including a processor and a memory; a program or instruction is stored in the memory, and the program or instruction is loaded and executed by the processor to implement the steps of the method for calculating the average lake water level in the above - mentioned embodiment.

[0084] This embodiment provides a computer - readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method for calculating the average lake water level in the above - mentioned embodiment are implemented.

Claims

1. A method for calculating the average water level of a lake, characterized in that, It includes the following steps: Step S1: Obtain the underwater DEM data of the lake area and the measured water level data of the water level stations in the lake area, and use each grid cell of the DEM as a calculation unit; Step S2: Combine the distribution of flood control projects in the lake area and the engineering design data of the gate opening, obtain the locations of each water level station and the flood control project control range, and derive the empirical average water level of the lake area; Step S3: Based on the underwater DEM data, obtain the static storage capacity of the lake under different water level conditions, and derive the water level-storage capacity relationship curve based on the current lake bottom topography; Step S4: According to the measured water level data of the water level stations and the underwater DEM data, calculate the water level of each grid cell in the lake area, and derive the dynamic storage capacity of the lake at each moment during the flood period; Dynamic storage of lake It is solved by the following formula: , In the formula, is the dynamic storage capacity of the lake at a certain moment, with the unit of m 3 , is the water depth of a grid cell in the lake area at a certain moment, with the unit of m, which is equal to the water level of the th grid cell in the underwater DEM data minus its lake bottom elevation, is the number of grid cells, is the spatial resolution of the calculation unit, which is 5m; Step S5: Use the calculation method of the average water level of the lake considering the dynamic storage capacity of the lake during the flood period to calculate the average water level; The calculation method of the average water level of the lake is: , In the formula, is the average water level of the lake at a certain moment, with the unit of m, is the active storage capacity of the lake at a certain moment, with the unit of m 3 , is the water level - storage capacity relationship function based on the current lake bottom topography determined by GIS through measuring the underwater DEM of the lake area. Combining with the DEM of the lake area, different water level values are respectively input in GIS to obtain the new water level - storage capacity relationship curve of the lake area, considering the influence of natural actions and human activities on the landform of the lake area.

2. The method for calculating the average water level of a lake according to claim 1, wherein The calculation method of the empirical average water level of the lake area described in Step S2 is: , In the formula, is the empirical average water level of the lake area obtained according to the empirical weight coefficient, with the unit of m, is the empirical weight coefficient, which is determined by the location of the water level station and the flood control project control range, is the measured water level of the j-th water level station, is the number of water level stations.

3. The method for calculating the average water level of a lake according to claim 1, wherein The calculation method of the static storage capacity of the lake under different water level conditions described in Step S3 is: , In the formula, is the static storage capacity of the lake under different water level conditions, with the unit of m. is the storage capacity calculated by the TIN generated by ARCGIS under different water level conditions, with the unit of m. 3 , is the different water levels input in GIS, with the unit of m, m is the number of TINs, and TIN is the irregular triangular network.

4. The method for calculating the average water level of a lake according to claim 1, wherein The water level calculation method for the grid cell is as follows: , In the formula, is the water level of the th grid cell, with the unit of m, is the measured water level of the water level station in the lake area, with the unit of m, represents the number of water level stations, is the distance weight from any grid cell in the lake area to a certain water level station.

5. The method for calculating the average water level of a lake according to claim 4, wherein The distance weight from any grid cell in the lake area to a certain water level station is obtained by solving the following formula: , where the distance weight is a function of the reciprocal of the distance is the distance from any grid cell in the lake area to a certain water level station, with the unit of m.

6. A device for calculating the average water level of a lake, characterized in that, It includes a processor and a memory; the memory stores programs or instructions, and the programs or instructions are loaded and executed by the processor to implement the steps of the method for calculating the average water level of the lake as described in any one of Claims 1 to 5.

7. A computer-readable storage medium, characterized in that, The programs or instructions are stored on the readable storage medium, and when the programs or instructions are executed by the processor, the steps of the method for calculating the average water level of the lake as described in any one of Claims 1 to 5 are implemented.

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