Method for estimating lake water volume change in combination with height measurement data and water level-volume curve

Abstract

The application provides a lake water volume change estimation method combining height measurement data and water level-volume curve, which has eight steps: step one, reading and processing of height measurement data; step two, extraction of lake water surface time sequence; step three, construction of lake area-water level curve; step four, lake water level interpolation during the period of missing height measurement data; step five, reordering of lake area; step six, fitting of area change-water level change relationship; step seven, estimation of lake water level change without height measurement data; and step eight, estimation of lake water storage change. In combination with satellite data and water level-volume curve, the lake water volume change during the period of missing height measurement data can be estimated, and long-time and continuous monitoring of lake water storage change is realized. The application belongs to the field of remote sensing hydrology and is suitable for monitoring of lake water level and water storage change.

Description

TECHNICAL FIELD

[0001] The application relates to a lake water volume change estimation method combining height measurement data and water level-volume curves, can solve the problem of estimating lake water volume change in a missing height measurement data period, develops an application mode of combining remote sensing technology and hydrological investigation in a data lacking area, belongs to the remote sensing hydrology field, and is suitable for lake water level and water volume change monitoring. BACKGROUND

[0002] Lakes are an important part of water resources, and the storage capacity change thereof can reflect the water balance state of a basin, diagnose the degree of environmental change, and is an important parameter for basin water resource evaluation and water balance analysis. Carrying out dynamic monitoring and investigation of lake storage capacity can provide important information for lake water resource utilization, water cycle and ecological environment process research.

[0003] Lake storage capacity change is usually estimated by combining lake area and water level change. In recent years, continuous improvement of satellite height measurement technology provides a new technical means for monitoring lake change. Compared with conventional measurement methods, radar height measurement satellites have the characteristics of real-time and all-weather, and laser height measurement satellites have high precision and accuracy, especially for lakes lacking hydrological observation stations, water level change can be dynamically monitored, and then lake storage change can be calculated. However, due to the limitation of satellite height measurement operation time and orbit characteristics, this method can only obtain the lake water level and storage capacity change in the period with height measurement data, and there is still a bottleneck in the time series monitoring of water level and storage capacity change in the area without height measurement data, and full coverage of the investigated lake cannot be achieved. SUMMARY

[0004] 1. Object: The object of the application is to provide a lake water volume change estimation method combining height measurement data and water level-volume curves, which can not only solve the problem of estimating lake water volume change in a missing height measurement data period, but also estimate the water level change of a lake without height measurement data according to a similarity parameter regionalization method, and realize long-time and continuous monitoring of lake storage capacity change.

[0005] 2. Technical problem to be solved

[0006] Due to the limitation of satellite height measurement operation time and orbit, the primary problem is how to interpolate the lake water level in the period with missing height measurement data to obtain long-time and continuous lake water level monitoring data, and the second problem is how to monitor the lake water level and storage capacity change for the lake not passing through the satellite.

[0007] 3. Technical scheme

[0008] The application provides a corresponding solution to the above technical problems. The overall solution is shown in the accompanying drawings. Figure 1The application is a lake water volume change estimation method combining height measurement data and water level-volume curve, and the specific steps are as follows:

[0009] Step one: reading and processing of height measurement data

[0010] Select and read the required height measurement satellite data source. According to the basic principle of satellite height measurement: the satellite orbit height is subtracted from the satellite-ground distance and a series of error corrections, and then the correction amount of the geoid to the reference ellipsoid is subtracted, and finally the lake water level based on the geoid is obtained. When the data amount of the lake surface in the same period is large, the data whose difference from the average value exceeds 3 times the error can be removed. The lake water level calculation formula is as follows,

[0011] Height = (Altitude-Range)-N geoid -C

[0012] Wherein, Height is the lake water level based on the geoid, Altitude is the satellite orbit height, Range is the satellite-ground distance, N geoid is the correction amount of the geoid to the reference ellipsoid, and C is various correction items, including solid tide correction, polar tide correction, atmospheric delay correction, etc.

[0013] Step two: extraction of lake water surface time series

[0014] Select and read the required medium-high resolution optical satellite remote sensing image data, and perform cloud removal and other preprocessing on it. The normalized water index is used to set the threshold to extract the time series lake water surface. The formula of the normalized water index is,

[0015] NDWI = [G-NIR] / [G+NIR]

[0016] Wherein, NDWI is the normalized water index, G is the green band reflectivity, and NIR is the near-infrared band reflectivity.

[0017] Step three: construction of lake "area-water level" curve

[0018] According to the exponential fitting function form (V = a·e (-Z / b) +cz, V is the volume, Z is the water level, and a, b, c are constants) of the water level-volume curve, the logarithmic relationship between the lake water level and the area can be derived. Select the lake area and water level near the satellite overflight time to establish the "area-water level" change curve of the lake (H = m·ln(A) +n, H is the water level, A is the water surface area, and m, n are constants).

[0019] Step four: lake water level interpolation in the period of missing height measurement data

[0020] For the period of missing height data, the lake area time series of the corresponding time series is substituted into the lake "area-water level" change curve to calculate.

[0021] Step five: reordering of lake area

[0022] The lake area time series is reordered according to the area size.

[0023] Step six: fitting of "area change- water level change" relationship

[0024] For the reordered lake "area- water level" sequence, the area change amount ΔA and the water level change amount ΔH sequence are calculated, and the fitting function ΔH = f (ΔA) is established.

[0025] Step seven: estimation of water level change amount of lake without height data

[0026] The similarity parameter regionalization method is adopted. It is assumed that the lake without height data and the lake with water level data in the same basin which is similar in distance and terrain has similar area- water level change characteristics. The area change amount ΔA of the lake without water level data is substituted into the function to obtain the water level change amount ΔH.

[0027] Step eight: estimation of lake water storage change amount

[0028] Based on the lake water level change amount and the lake area, the trapezoidal cylindrical volume formula is used to calculate the lake water storage change amount ΔV. The trapezoidal cylindrical volume formula is,

[0029]

[0030] Where, ΔV i is the lake water storage change amount at i period, A i and A i-1 are the lake water surface areas at i period and i-1 period respectively, and ΔH is the lake water level change amount at i period and i-1 period respectively.

[0031] 4. Advantages and effects

[0032] The lake water volume change estimation method combining height data and water level- volume curve has the following advantages: (1) the lake water level of the period of missing height data is interpolated to obtain long-time and continuous lake water level monitoring data, and the problem of lake water storage change monitoring in the period of missing data is solved; (2) for the lake which is not passed through by the height satellite, the water level change amount is estimated according to the area change amount based on the similarity parameter regionalization method, and the lake water storage change monitoring of the lake without data is realized. DETAILED DESCRIPTION

[0033] Figure 1The implementation flowchart of the lake water volume change estimation method combined with height measurement data and water level-volume curve of the application.

[0034] Figure 2 The time series of measured height water level and lake area of L1 lake.

[0035] Figure 3 The "area-water level" curve of L1 lake.

[0036] Figure 4 The interpolated water level time series of L1 lake.

[0037] Figure 5 The fitting relationship of "area change amount-water level change amount" of L1 lake.

[0038] Figure 6 The annual storage change estimation results of L1 lake (with height measurement data) from 2000 to 2021.

[0039] Figure 7 The annual storage change estimation results of L2 lake (without height measurement data) from 2000 to 2021. DETAILED DESCRIPTION

[0040] In order to better illustrate the lake water volume change estimation method combined with height measurement data and water level-volume curve, two lakes L1 and L2 in the inland river basin of Inner Mongolia were selected as the implementation examples of lake water level and storage change estimation from 2000 to 2021, wherein L1 lake has height measurement data and L2 lake has no height measurement data. The specific steps are as follows:

[0041] Step one: reading and processing of height measurement data

[0042] Read and process the height measurement data ICESat (2003.2-2009.10) and ICESat-2 (2018.10-2021.12) in the study area. Subtract the satellite distance from the satellite altitude and a series of error corrections, and then subtract the correction amount from the geoid to the reference ellipsoid to finally obtain the lake water level based on the geoid. When the data amount of the lake surface in the same period is large, the data whose difference from the average value exceeds 3 times the standard error can be removed (as shown in the attached Figure 2 The lake water level calculation formula is as follows,

[0043] Height = (Altitude - Range) - N geoid -C

[0044] Wherein, Height is the lake water level based on the geoid, Altitude is the satellite altitude, Range is the satellite distance from the ground, N geoidThe correction amount from the geoid to the reference ellipsoid, where the EGM2008 geoid is used, and C is various correction terms, including solid tide correction, polar tide correction, atmospheric delay correction, etc.

[0045] Step two: lake water surface time series extraction

[0046] Read and process high-resolution optical satellite remote sensing images Landsat5 / 7 / 8, Sentinel-2A / 2B data in the study area, and preprocess them such as cloud removal. Use the normalized water index to set the threshold to extract the time series lake water surface (as shown in the accompanying Figure 2 The formula of the normalized water index is NDWI = [G-NIR] / [G+NIR]

[0047] Where NDWI is the normalized water index, G is the green band reflectivity (around 550 nm), and NIR is the near-infrared band reflectivity (around 850 nm).

[0048] Step three: construction of lake "area-water level" curve

[0049] As shown in the accompanying Figure 2 L1 lake obtained from step one includes only 16 ICESat data and 7 ICESat-2 data on a monthly scale, and is not continuous. According to the exponential fitting function form of the water level-volume curve (V = a·e (-Z / b) +c, V is the volume, Z is the water level, a, b, c are constants), it can be deduced that the lake water level and area are in logarithmic relationship. Select the lake area and water level with similar satellite overpass time to establish the "area-water level" change curve of the lake (H = 2.5422·ln(A) + 1399.4, H is the water level, A is the water area) (as shown in the accompanying Figure 3

[0050] Step four: lake water level interpolation for missing altimetry data period

[0051] For the period of missing altimetry data, the lake area corresponding to the time series is substituted into the "area-water level" change curve of the lake in step three to calculate the lake water level in the period of missing altimetry data. As shown in the accompanying Figure 4 L1 lake water level data from 2000.01 to 2021.12 can be obtained.

[0052] Step five: lake area reordering

[0053] The lake area time series of L1 is sorted in descending order of area size using the sorting function of Excel. This processing is for step six to eliminate the time attribute of the "area-water level" data.

[0054] ​Step Six: Fitting the Relationship Between "Area Change - Water Level Change"

[0055] For the reordered "area-water level" sequence of Lake L1, the changes in area ΔA and water level ΔH were calculated separately, and a fitting function ΔH = 0.4206 * ΔA - 0.0096 was established, as shown in the attached figure. Figure 5 As shown, the change in lake area ΔA can be substituted into this function to deduce the change in water level.

[0056] Step 7: Estimation of Lake Water Level Changes Without Height Measurement Data

[0057] A similarity parameter regionalization method is employed. It is assumed that lake L2, lacking altimeter data, and lake L1, which is geographically close and topographically similar within the same basin but has altimeter data, exhibit similar area-water level change characteristics. The area change ΔA of lake L2 is substituted into the fitting function from step six to obtain its water level change ΔH.

[0058] Step 8: Estimation of Lake Water Storage Changes

[0059] Based on the lake's water level change and area, the trapezoidal cylinder volume formula is used to calculate the lake's water storage change ΔV. The trapezoidal cylinder volume formula is as follows:

[0060]

[0061] Wherein, △V i Let A be the change in lake water storage during time period i. i and A i-1 ... Figure 6 and attached Figure 7 These are the estimated annual water storage changes for lake L1 (with available elevation data) and lake L2 (without available elevation data) from 2000 to 2021.

Claims

1. A method for estimating changes in lake water volume combining bathymetric data and water level-volume curves, characterized in that, The method comprises the following steps: Step one: reading and processing of the height data Select and read the required satellite data source; subtract the satellite distance from the ground and a series of error corrections from the satellite orbital height, and then subtract the correction amount from the geoid to the reference ellipsoid to finally obtain the lake water level based on the geoid; Step two: extraction of the lake water surface time series Select and read the required medium-high resolution optical satellite remote sensing image data, preprocess it to remove clouds, and use the normalized water index to set the threshold to extract the time series of the lake water surface; Step three: construction of the lake "area-water level" curve According to the exponential fitting function form of water level-volume curve, the logarithmic relationship between lake water level and area is derived; the lake area and water level with similar satellite transit time are selected to establish the "area-water level" change curve of the lake; the exponential fitting function form of water level-volume curve is: V=a·e (-Z / b) +c, V is the volume, Z is the water level, a, b, c are constants; the "area-water level" change curve of the lake is: H=m·ln(A)+n, H is the water level, A is the water surface area, m, n are constants; Step four: interpolation of the lake water level in the period of missing height data For the period of missing height data, the corresponding time series of the lake area is substituted into the "area-water level" change curve of the lake to calculate it; Step five: reordering of the lake area The lake area time series is reordered according to the area size; Step six: fitting of the "area change amount-water level change amount" relationship The reordered lake "area-water level" sequence is calculated to obtain the area change amount △A and the water level change amount △H sequence, and the fitting function △H=f(△A) is established; Step seven: estimation of the lake water level change amount without height data The similarity parameter regionalization method is adopted; it is assumed that the lake without height data and the lake with water level data in the same basin with similar distance and terrain have similar area-water level change characteristics; the area change amount △A of the lake without water level data is substituted into the function to obtain the water level change amount △H; Step eight: estimation of the lake water storage change amount Based on the lake water level change amount and the lake area, the trapezoidal cylindrical volume formula is used to calculate the lake water storage change amount △V.

2. The method for estimating lake water volume change by combining altimetry data and water level-storage curve of claim 1, wherein: In step one, when the data amount of the lake surface in the same period is large, the data with a difference of more than 3 times the mean error from the average value is removed; the lake water level calculation formula is as follows, Height = (Altitude - Range) - N geoid -C where Height is the lake water level based on the geoid, Altitude is the satellite orbit height, Range is the satellite to ground distance, N geoid is the correction from the geoid to the reference ellipsoid, and C is various correction terms including solid tide correction, polar tide correction, and atmospheric delay correction.

3. The method for estimating lake water volume change by combining altimetry data and water level-storage curve of claim 1, wherein: In step two, the formula of the normalized water index is as follows, NDWI=[G-NIR] / [G+NIR] Wherein, NDWI is the normalized water index, G is the green band reflectivity, and NIR is the near-infrared band reflectivity.

4. The method for estimating lake water volume change by combining altimetry data and water level-storage curve of claim 1, wherein: In step eight, the trapezoidal cylindrical volume formula is as follows, Wherein, ΔV i is the water storage change of the lake in the i period, A i and A i-1 are the water surface areas of the lake in the i period and the i-1 period respectively, and ΔH is the water level change of the lake in the i period and the i-1 period respectively.

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