An integrated method for constructing and analyzing long series of regional rainfall characterizations

Abstract

This invention relates to the field of rainfall data analysis technology and discloses an integrated method for constructing and analyzing a long series of regional rainfall characterization data. The invention includes: acquiring rainfall stations, selecting rainfall stations, selecting representative rain gauges, constructing a long series of rainfall characterization data for the region to be analyzed, and performing representative analysis of the long series. The overall method of this invention is rationally designed, effectively acquiring the required rainfall stations through drought and flood distribution atlases; utilizing methods such as IDW to comprehensively achieve data interpolation of rainfall; calculating the average drought and flood levels of the region to be analyzed year by year, effectively constructing a long series of rainfall characterization data for the region to be analyzed from 1470 to the present; and effectively achieving representative analysis of the measured rainfall series for the region to be analyzed using this long series of rainfall characterization data from 1470 to the present. The overall system of this invention is easy to implement and applicable to various regions to be analyzed.

Description

Technical Field

[0001] This invention relates to the field of rainfall analysis technology, specifically to an integrated method for constructing and analyzing long-series regional rainfall characterization. Background Technology

[0002] When analyzing the rainfall characteristics of a region based on measured rainfall data, it is necessary to consider which period's measured rainfall series can best represent the region's rainfall variation. This series should include both years with low and high rainfall, and should represent the overall characteristics of the region's multi-year rainfall variation, providing a good representation of the overall distribution. Since the total population is unknown, generally speaking, the longer the series, the more possible combinations of information the sample contains, resulting in better representativeness and smaller sampling error. Currently, since the advent of measured rainfall data, rainfall series have typically only covered 50 to 70 years. Whether this length of measured rainfall data series can fully represent the overall characteristics of the region's multi-year rainfall variation needs to be corroborated by longer data series closely related to rainfall.

[0003] On the other hand, water conservancy project design requires the development of design runoff and design sediment for the project location, which directly determines the scale and investment of the water conservancy project. To develop more scientifically sound and reasonable design runoff and design sediment results, it is also necessary to analyze the representativeness of the runoff and sediment series. The abundance and scarcity of runoff and sediment are closely related to rainfall. By demonstrating the representativeness of the rainfall series in the relevant area, the representativeness analysis of the runoff and sediment series can be supported, thereby providing assistance for the planning and design of water conservancy projects. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides an integrated method for constructing and analyzing long-series regional rainfall characterization.

[0005] The technical solution of this invention is: an integrated method for constructing and analyzing long-series regional rainfall characterization, comprising:

[0006] S1, Obtain rainfall stations

[0007] Collect measured rainfall data in the area to be measured, and obtain rainfall stations from the drought and flood distribution map set;

[0008] S2, Selecting rainfall stations

[0009] Based on the rainfall stations, Thiessen polygons are used to divide the boundary map of the area to be measured, and then rainfall stations are selected.

[0010] S3. Select representative rain gauge stations

[0011] From the selected rainfall stations, further select those with continuous rainfall data and good spatial representativeness as representative rainfall stations;

[0012] S4. Construct a long series of rainfall characterization for the area to be measured.

[0013] For drought and flood level data representing rain gauge stations from 1470 to 1959, interpolation was performed using station data from the drought and flood distribution atlas and the IDW method.

[0014] For drought and flood level data representing rain gauge stations from 1960 to the present, the measured rainfall was converted according to the precipitation classification expression given by the drought and flood distribution atlas. The Thiessen polygon method was used to calculate the average drought and flood level of the area under test year by year, and then a long series of rainfall characterization of the area under test from 1470 to the present was constructed.

[0015] S5, Representative Analysis of Rainfall Series

[0016] Based on the long series of rainfall characteristics of the area to be measured from 1470 to the present constructed in step S4, multiple methods were used to analyze the representativeness of the measured rainfall series of the area to be measured.

[0017] Further, step S2 specifically involves: dividing the boundary map of the area to be tested into Thiessen polygons based on the rainfall stations, and deleting the rainfall stations with a weight coefficient of 0, with the remainder being the selected rainfall stations; obtaining Thiessen polygon blocks within the area to be tested through Thiessen polygon division, effectively excluding rainfall stations with a weight coefficient of 0.

[0018] Furthermore, step S3 specifically involves selecting representative rainfall stations from the selected rainfall stations, using the average drought and flood level as the selection criterion. Selecting representative rainfall stations can effectively improve the efficiency of analyzing the abundance and scarcity of rainfall in the area to be measured.

[0019] Furthermore, step S4, which uses the IDW method for interpolation, specifically involves finding the 10 closest rainfall stations to the representative rainfall station as reference stations, and then applying the formula... The rainfall value of the representative rain gauge is calculated using the reciprocal of the square of the distance between the representative rain gauge and the reference station as the weight. The closer the representative rain gauge is to the reference station, the larger the weight coefficient. Here, p represents the rainfall value of the station to be interpolated, d represents the distance between the stations, and P... i The i-th reference station represents the drought and flood level; by using the inverse square distance method, spatial interpolation can be performed to calculate the average drought and flood level of the area under test year by year, effectively constructing a long series of rainfall characteristics of the area under test from 1470 to the present.

[0020] Furthermore, the IDW method described in step S4 can be replaced by the Kriging method, the inverse square distance method, the multiple regression method, or the thin plate spline function method; based on the actual situation of the area to be measured, an appropriate calculation method is selected from multiple methods to make the method more practical and applicable to various regional environments.

[0021] Furthermore, the precipitation classification expression in step S4 is specifically as follows:

[0022]

[0023] Among them, the precipitation classification expression R represents the multi-year average rainfall from May to September. i The σ represents the annual rainfall from May to September, and the standard deviation is σ. Using precipitation data, the original classification method, which used proportional relationships, is converted into a formula that uses the multi-year average precipitation and the standard deviation σ, so that these 5 levels can be respectively associated with precipitation, making the quantitative meaning clearer.

[0024] Furthermore, the analytical method described in S5 employs one or more of the following: comparison of mean and Cv, modulus ratio coefficient difference product curve method, moving average method, and modulus ratio coefficient cumulative average curve method. Multiple methods enable more comprehensive analytical results.

[0025] Compared with existing technologies, the beneficial effects of this invention are as follows: the overall method of this invention is reasonably designed, and the required rainfall stations can be effectively obtained through drought and flood distribution maps; the Thiessen polygon division of the boundary map of the area to be measured enables targeted selection of rainfall stations; the selection criteria for representative rain gauges can be used to further select representative rain gauges from the rainfall stations; the IDW method is used to achieve data interpolation of rainfall; the average drought and flood level of the area to be measured is calculated year by year, effectively constructing a long series of rainfall characteristics of the area to be measured from 1470 to the present; the long series of rainfall characteristics of the area to be measured from 1470 to the present effectively realizes the representative analysis of the measured rainfall series of the area to be measured; the overall system of this invention is easy to implement and is applicable to the analysis of various areas to be measured. Attached Figure Description

[0026] Figure 1 This is a system module framework diagram of the present invention;

[0027] Figure 2 This is an example of a Thiessen polygon segmentation map of rainfall stations in the Yellow River Basin;

[0028] Figure 3 This is a map showing the spatial distribution of representative rain gauges and selected rainfall stations in the Helong area;

[0029] Figure 4 This is an example of a long series of rainfall characterization maps from 1470 to 2022 in the Helong Interval.

[0030] Figure 5 This is an example of the application of the drought and flood level series modulus coefficient difference product curve of the Helong interval from 1470 to 2022;

[0031] Figure 6This is an example of a 10-period moving average curve of drought and flood levels in the Helong area from 1470 to 2022.

[0032] Figure 7 This is an application example of the cumulative average curve of the drought and flood level series modulus ratio from 1470 to 2022 in the Helong area. Detailed Implementation

[0033] The present invention will now be described in more detail with reference to specific embodiments, so as to better demonstrate the advantages of the present invention.

[0034] Example:

[0035] like Figure 1 The method shown is an integrated approach for constructing and analyzing long-series regional rainfall characterizations, specifically including:

[0036] S1, Obtain rainfall stations

[0037] Collect measured rainfall data in the area to be measured, and obtain rainfall stations from the drought and flood distribution map set;

[0038] S2, Selecting rainfall stations

[0039] The boundary map of the area to be measured is divided into Thiessen polygons based on rainfall stations, and rainfall stations are selected accordingly. The boundary map of the area to be measured is divided into Thiessen polygons based on rainfall stations, and the rainfall stations with a weight coefficient of 0 are deleted, and the rest are the selected rainfall stations.

[0040] S3. Select representative rain gauge stations

[0041] From the selected rainfall stations, the average drought and flood level was used as the selection index to further select rainfall stations with continuous rainfall data and good spatial representativeness as representative rainfall stations.

[0042] S4. Construct a long series of rainfall characterization for the area to be measured.

[0043] For drought and flood level data of representative rain gauge stations from 1470 to 1959, station data from the drought and flood distribution atlas were used, and interpolation was performed using the IDW method. The IDW interpolation method specifically involves finding the 10 closest rainfall stations to the representative rain gauge station as reference stations, and then applying the formula... The rainfall value of the representative rain gauge is calculated using the reciprocal of the square of the distance between the representative rain gauge and the reference station as the weight. The closer the representative rain gauge is to the reference station, the larger the weight coefficient. Here, p represents the rainfall value of the station to be interpolated, d represents the distance between the stations, and P... iThis represents the drought / flood level of the i-th reference station. For drought / flood level data representing rain gauge stations from 1960 to the present, the measured rainfall is converted according to the precipitation classification expression given in the drought / flood distribution atlas. The Thiessen polygon method is used to calculate the average drought / flood level of the area under test year by year, and then a long series of rainfall characteristics for the area under test from 1470 to the present is constructed. The precipitation classification expression given in the drought / flood distribution atlas is as follows:

[0044]

[0045] Among them, the precipitation classification expression R represents the multi-year average rainfall from May to September. i This represents the annual rainfall from May to September, with σ being the standard deviation.

[0046] Among them, the drought and flood distribution atlas is specifically the "Atlas of Drought and Flood Distribution in China over the Past 500 Years" edited by the Chinese Academy of Meteorological Sciences;

[0047] S5, Representative Analysis of Rainfall Series

[0048] Based on the long series of rainfall characteristics of the area to be measured from 1470 to the present constructed in step S4, multiple methods were used to analyze the representativeness of the measured rainfall series of the area to be measured. The specific analysis methods used were mean and comparison, modulus ratio coefficient difference product curve method, moving average method, and modulus ratio coefficient cumulative average curve method.

[0049] Application example:

[0050] Using the methods described in the above embodiments, and taking the Helong interval as the research object, an analytical method based on long-series regional characterization was established. The Helong interval refers to the area from Hekou Town to Longmen in the middle reaches of the Yellow River. In this study, stations involved in the Helong interval were selected from the "Atlas of Drought and Flood Distribution in China over the Past 500 Years" as the rainfall stations used in this analysis. For example... Figure 2 As shown, the Yellow River Basin boundary map is divided into Thiessen polygons using 120 stations from the "Atlas of Drought and Flood Distribution in China over the Past 500 Years", and a total of 30 stations are selected.

[0051] Twenty-three rain gauges with continuous rainfall data from 1960 to 2016 and good spatial representativeness were selected as representative stations in the Helong area; for example... Figure 3 The image shows the distribution of rain gauge stations and selected stations from the "Atlas of Drought and Flood Distribution in China over the Past 500 Years";

[0052] For drought and flood level data of representative rain gauge stations from 1470 to 1959, station data from the "Atlas of Drought and Flood Distribution in China over the Past 500 Years" were used, and data interpolation was performed using the IDW method; spatial interpolation was performed using the inverse square distance method.

[0053] For drought and flood level data representing rain gauge stations from 1960 to 2022, the measured rainfall was converted according to the precipitation classification expression given in the "Atlas of Drought and Flood Distribution in China over the Past 500 Years". The Thiessen polygon method was used to calculate the average drought and flood level of the Helong area year by year, as follows: Figure 4 As shown, a long series of rainfall characterization data for the Helong region from 1470 to 2022 was constructed.

[0054] The representativeness of the rainfall series in the Helong area from 1966 to 2022 was analyzed by comparing the mean and Cv, using the difference product curve method of modulus coefficient, the moving average method, and the cumulative average curve method of modulus coefficient.

[0055] Based on previous findings, the mean and Cv of the drought and flood levels of the Helong interval during common representative periods in water and sediment change research were statistically analyzed, as shown in Table 1.

[0056] Table 1: Comparison of mean and CV values ​​of drought and flood severity levels in the Helong area at different times

[0057] period mean Cv 1470–2022 3.17 0.26 1956-1970 2.83 0.36 2000-2022 2.66 0.29 2007-2022 2.47 0.31 1966–2022 2.99 0.28

[0058] Conclusion: As can be seen from Table 1, the average drought and flood levels and Cv of the 1966-2022 series are closest to those of the 1470-2022 series, with a difference of no more than 9%, indicating that the drought and flood levels of the 1966-2022 series are relatively representative.

[0059] The modulus coefficient difference curve, 10-day moving average curve, and cumulative average curve of the drought and flood levels in the Helong area from 1470 to 2022 are shown below. Figure 5 , 6 As shown in Figure 7; from Figure 5 , 6 It can be seen that the series of drought and flood levels from 1966 to 2022 covers all periods of abundance, normal conditions, and drought; from Figure 7 It can be seen that the cumulative average value of the modulus ratio around 1979 has basically stabilized, indicating that the rainfall series representing the Helong area needs at least 40 years of support, and the drought and flood levels of the series from 1966 to 2022 are relatively representative.

Claims

1. A method for integrated construction and analysis of long-series regional rainfall characterization, characterized in that, include: S1, Obtain rainfall stations Collect measured rainfall data in the area to be measured, and obtain rainfall stations from the drought and flood distribution map set; S2, Selecting rainfall stations Based on the rainfall stations, Thiessen polygons are used to divide the boundary map of the area to be measured, and then rainfall stations are selected. S3. Select representative rain gauge stations From the selected rainfall stations, further select those with continuous rainfall data and good spatial representativeness as representative rainfall stations; S4. Construct a long series of rainfall characterization for the area to be measured. For drought and flood level data representing rain gauge stations from 1470 to 1959, drought and flood distribution atlas station data were used, and comprehensive interpolation was performed using methods such as IDW. For drought and flood level data representing rain gauge stations from 1960 to the present, the measured rainfall was converted according to the precipitation classification expression given by the drought and flood distribution atlas. The Thiessen polygon method was used to calculate the average drought and flood level of the area under test year by year, and then a long series of rainfall characterization of the area under test from 1470 to the present was constructed. The expression for rainfall level and precipitation classification ； ； ； ； ； Among them, the precipitation classification expression This represents the multi-year average rainfall from May to September. This represents the annual rainfall from May to September, with σ being the standard deviation. S5, Representative Analysis of Rainfall Series Based on the long series of rainfall characteristics of the area to be measured from 1470 to the present constructed in step S4, multiple methods were used to analyze the representativeness of the measured rainfall series.

2. The integrated method for constructing and analyzing long-series regional rainfall characterizations according to claim 1, characterized in that, Step S2 specifically involves: dividing the boundary map of the area to be measured into Thiessen polygons based on the rainfall stations, and deleting the rainfall stations with a weight coefficient of 0, with the remainder being the selected rainfall stations.

3. The integrated method for constructing and analyzing long-series regional rainfall characterizations according to claim 1, characterized in that, Step S4, which uses methods such as IDW for comprehensive interpolation, specifically involves finding the 10 closest rainfall stations to the representative rainfall station as reference stations, and then applying the formula... The rainfall value of the representative rain gauge is calculated using the reciprocal of the square of the distance between the representative rain gauge and the reference station as the weight. The closer the representative rain gauge is to the reference station, the larger the weight coefficient. Where p represents the rainfall value of the station to be interpolated, and d represents the distance between stations. This indicates the drought / flood level of the i-th reference station.

4. The integrated method for constructing and analyzing long-series regional rainfall characterizations according to claim 1, characterized in that, The IDW method described in step S4 can be replaced by the Kriging method, the inverse squared distance method, the multiple regression method, or the thin plate spline function method.

5. The integrated method for constructing and analyzing long-series regional rainfall characterizations according to claim 1, characterized in that, The analytical method described in S5 employs one or more of the following: mean and comparison, modulus coefficient difference product curve method, moving average method, and modulus coefficient cumulative average curve method.

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