阅读说明：本技术 一种用于定量海绵效应的径流频谱相似度计算方法及其应用 (Runoff frequency spectrum similarity calculation method for quantifying sponge effect and application thereof ) 是由 王晟 闵飞田 黄鹏飞 于 2021-05-26 设计创作，主要内容包括：本发明提供一种用于定量海绵效应的径流频谱相似度计算方法,包括以下步骤：获取长时间序列的径流量日值数据,生成径流频谱矩阵以表征径流特征；生成具有分别代表自然地貌和海绵城市的X矩阵和Y矩阵的径流频谱图,反映径流特征的差异；不计算图形相似,直接计算矩阵X和矩阵Y的相似度,将X矩阵和Y矩阵中累积频率不同的流量移动到最接近的频率位置上,使X矩阵和Y矩阵的累积频率对齐,然后计算对齐后的X矩阵和Y矩阵的相似度,根据每组可比对的差异度和水量权重计算对齐后的矩阵X和Y矩阵的相似度,它代表自然径流特征修复程度；径流频谱可以用于建设效果评价,也可以用于工程方案寻优,分别计算不同开发方案对自然径流特征的修复程度。(The invention provides a runoff frequency spectrum similarity calculation method for quantifying a sponge effect, which comprises the following steps of: acquiring runoff daily value data of a long-time sequence, and generating a runoff frequency spectrum matrix to represent runoff characteristics; generating a runoff spectrogram with an X matrix and a Y matrix respectively representing a natural landform and a sponge city, and reflecting the difference of runoff characteristics; calculating the similarity of a matrix X and a matrix Y directly without calculating graph similarity, moving the flow with different accumulated frequencies in the X matrix and the Y matrix to the closest frequency position to align the accumulated frequencies of the X matrix and the Y matrix, then calculating the similarity of the aligned X matrix and the aligned Y matrix, and calculating the similarity of the aligned X matrix and the aligned Y matrix according to the contrastive difference and the water quantity weight of each group, wherein the similarity represents the nature runoff characteristic repairing degree; the runoff frequency spectrum can be used for evaluating the construction effect and optimizing the engineering scheme, and the restoration degree of the natural runoff characteristics by different development schemes is calculated respectively.)

1. A runoff frequency spectrum similarity calculation method for quantifying a sponge effect is characterized by comprising the following steps:

s1: acquiring runoff daily value data of a long-time sequence to generate a runoff frequency spectrum matrix

S2: generating a digitized runoff frequency matrix representing the natural landform and the sponge city respectively: drawing a runoff frequency spectrogram by an X matrix and a Y matrix, wherein the similarity of the X matrix and the Y matrix represents the natural runoff characteristic restoration degree;

s3: calculating runoff frequency spectrum similarity:

s31: representing the graphical runoff spectrum by the digitized runoff frequency matrix:

and

wherein X is an n row 2 column matrix and Y is an m row 2 column matrix;andthe runoff is sorted from large to small, and the unit is mm/d; i/T represents the cumulative frequency and the radial flow x_iAnd y_iThe frequency location of the location; n and m represent total runoff event occurrence days in units of d; t is the number of statistical years and has the unit of y; the n/T and the m/T are maximum cumulative frequencies and represent matrix lengths;

s32: moving the traffic with different accumulated frequencies in the X matrix and the Y matrix to the nearest frequency position to align the accumulated frequencies of the X matrix and the Y matrix;

s33: comparing the aligned X matrix with the aligned Y matrix, wherein the runoff quantity of the X matrix and the runoff quantity of the Y matrix corresponding to the same frequency position are called as comparison, and directly calculating the comparison difference of each group;

s34: and calculating the similarity of the aligned X matrix and Y matrix according to the comparable difference and the water quantity weight of each group, wherein the similarity represents the natural runoff characteristic restoration degree.

2. The runoff frequency spectrum similarity calculation method for quantifying the sponge effect as claimed in claim 1, wherein the runoff rate refers to the runoff rate outside the earth surface of a research site, is obtained through on-line monitoring and model simulation, and is carried out according to the requirements in the sponge city construction evaluation standard GB/T51345-2018.

3. The runoff spectrum similarity calculation method for quantifying the sponge effect as recited in claim 1, wherein the step of S2 comprises the steps of:

s21: the daily runoff value obtained by on-line monitoring and simulation using a model is usually m³D, recorded, divided by the area of the field to give units mm/d; considering that the recording precision of rainfall is 0.1mm/d, further rounding off the radial flow to take 1-digit effective number after decimal point, and making the unit and precision of the radial flow consistent with the unit and precision of the rainfall;

s22: drawing a runoff frequency spectrum: and sequencing all the runoff quantities from large to small, counting the cumulative occurrence times of a certain runoff quantity, and dividing the cumulative occurrence times by the years of a counting time interval to obtain the cumulative frequency. And drawing by taking the runoff as an abscissa and the cumulative frequency as an ordinate to obtain a runoff spectrogram.

The X matrix and the Y matrix respectively represent a natural landform and a runoff frequency spectrum of a sponge city, and the similarity of the X matrix and the Y matrix is the natural runoff characteristic restoration degree and is used for quantifying the sponge effect.

4. A runoff spectrum similarity calculating method for quantifying the sponge effect as set forth in claim 2 wherein in the step S22, in order to highlight the large runoff events when plotting the cumulative frequency as the ordinate, the logarithmic coordinate is used as the ordinate.

5. The runoff spectrum similarity calculation method for quantifying the sponge effect as recited in claim 1, wherein the step of S32 comprises the steps of:

s321: aligning the Y matrix to the X matrix: sequentially searching each frequency in the Y matrix to be equal to or smaller than the maximum value thereof in the X matrix as a frequency position to be aligned; merging the traffic to be aligned to the same frequency position into a new value by the following method:

the number of days of occurrence of the new traffic equals the sum of the number of days of occurrence of the combined traffic, i.e., ∑ (y)_iNumber of days of onset + y_i+1Days of occurrence + …); after the treatment, the total runoff and the total occurrence days of Y are kept unchanged;

s322: the method of step S321 is adopted to align the X-aligned Y.

6. The method for calculating the runoff spectral similarity for quantifying the sponge effect as recited in claim 1, wherein each set of the comparable dissimilarity calculation formula in the step S33 is as follows:

absolute degree of difference ═ y_i/T-x_i/T|

Relative degree of difference ═ y_i/T-x_i/T|/x_i/T。

7. The method for calculating the runoff spectrum similarity for quantifying the sponge effect as claimed in claim 1, wherein the calculation formula for calculating the similarity of the aligned X matrix and Y matrix according to the comparable difference and the water weight in step S34 is as follows:

similarity is 1-sigma (relative difference degree)₁Water flow weight₁+ … + relative degree of difference_iWater flow weight_i+ … + relative degree of difference_nWater flow weight_n)

The runoff frequency spectrum matrix similarity is obtained through calculation of the formula; the closer the similarity is to 1, the more similar the two radial flow spectrum matrixes are, and the two matrixes are completely the same if the similarity is equal to 1; the X matrix represents a natural landform and is a reference matrix, and the Y matrix represents a sponge city and is a matrix to be compared; if more than 1 matrix is to be compared, e.g., multiple development scenarios are available in the same site, the X matrix must be the longest matrix length.

8. The runoff spectrum similarity calculation method for quantifying the sponge effect as recited in claim 7, wherein the water amount weight is calculated according to the aligned X, and the water amount weight that can be compared in the ith group is calculated as follows:

water volume weight_iWhich represents the proportion of the runoff at frequency location i/T in the total runoff and determines the contribution of each alignable matrix discrepancy.

9. The runoff spectrum similarity calculation method for quantifying the sponge effect as recited in claim 1, wherein the above algorithm is implemented by Microsoft Excel or programming language.

10. Use of a runoff spectrum similarity calculation method according to any one of claims 1 to 9 for quantifying the sponge effect, wherein the obtained runoff spectrum is used for construction effect evaluation or engineering project optimization.

Technical Field

The invention relates to the technical field of sponge city construction, in particular to a runoff frequency spectrum similarity calculation method for quantifying a sponge effect and application thereof.

Background

The urbanization process generates a large number of impervious surfaces, which destroy natural hydrological conditions and prevent rainwater from infiltrating into soil during rainfall, thus causing large increase of surface runoff and runoff pollutant discharge, and causing urban waterlogging and water environment quality deterioration. To solve the problem, China proposes to build sponge cities, and starts to support the sponge cities by central finance in 2015 to build test points.

The basic connotation of sponge city construction is that low impact development technical measures (LID) are comprehensively taken through city planning and construction management and control, urban rainfall runoff is effectively controlled, and damage of urban development and construction behaviors to original natural hydrological features and water ecological environment is reduced to the maximum extent. The sponge effect refers to the natural hydrological feature maintenance and restoration effect realized by sponge city construction. How to quantify the extent of restoration of natural hydrologic features? The problem is a key problem in sponge city scheme decision and effect evaluation.

Solving this problem involves two aspects: firstly, how to characterize the hydrological features and secondly how to quantify the restoration degree of the natural hydrological features. The difficulty is that hydrologic events have uncertainty.

The direct effect of the impervious surface is to increase surface runoff, which is the origin of other problems, so the hydrological features are often replaced with runoff features. The current method mainly adopts a total annual runoff quantity control rate to characterize runoff characteristics. The annual runoff total control rate refers to the ratio of the annual average rainfall to the annual average rainfall which is controlled (not discharged outside). The method uses the annual runoff total control rate to express the runoff characteristics. Under the condition of technical economy and feasibility, the annual runoff total control rate of the sponge city should be as close as possible to the natural runoff total control rate. That is, the closeness degree of the urban annual runoff total amount control rate and the natural runoff total amount control rate reflects the restoration degree of the natural hydrological characteristics.

The annual runoff total control rate is calculated based on a plurality of rainfall runoff events of a long-time sequence, uncertainty is covered, and the method for calculating the runoff total is simple and easy to learn, so that the method plays an important role in promoting sponge city construction in the early stage of the sponge city construction.

As the understanding of the sponge city deepens, the disadvantages of the method gradually appear: the annual runoff total control rate is lack of details, and the resolution is not high enough. Runoff events are usually recorded by daily values, runoff rate of one place can be greatly different on different days, annual runoff total control rate smoothes the differences, the sponge effect cannot be analyzed on time resolution of days, and daily value and frequency analysis of the runoff rate cannot be carried out.

The U.S. National environmental protection agency (USEPA) issued National rainwater Calculator software (National storm water Calculator, EPA/600/R-13/085) in 2013, which proposed characterizing the runoff characteristics of sponge cities by runoff spectra. The runoff frequency spectrum generation method comprises the following steps: and sorting all the daily values of the runoff volume from large to small, counting the cumulative occurrence times of a certain flow volume, and dividing the cumulative occurrence times by the analysis years to obtain the cumulative excess frequency, which is called cumulative frequency for short. The runoff rate daily value is used as an abscissa, and the accumulated frequency is used as an ordinate to obtain a runoff spectrum, which is shown in an attached figure 8 of the specification.

The upper graph presents all runoff events in a frequency order, just like a spectrum, and is therefore called a runoff spectrum. Taking the X matrix in the figure as an example, the abscissa 29.2mm/d corresponds to the ordinate 2d/y, meaning that runoff events of 29.2mm/d or more occur on average twice a year. On the X matrix, the maximum radial flow rate is 147.2mm/d, and the cumulative frequency is 0.037 d/y; minimum runoff 0.1mm/d, cumulative frequency 32.593 d/y. As can be seen from the figure, the runoff frequency spectrum completely presents the flow, the frequency and the distribution rule of all runoff events, and the runoff characteristics are represented on the time resolution of days. And the annual runoff total control rate is calculated by the annual average runoff quantity, and compared with the annual average runoff quantity, the runoff frequency spectrum greatly improves the analysis capability of runoff characteristics.

More importantly, an X matrix and a Y matrix in the map are set to represent a natural landform and a runoff frequency spectrum of the sponge city respectively, and the restoration degree of the sponge city to the natural runoff characteristics can be evaluated by comparing the similarity of the X matrix and the Y matrix. Therefore, the runoff spectrum has important significance for researching the sponge effect. Although the idea of evaluating the restoration effect of the natural runoff characteristics by using the runoff frequency spectrum has been proposed in 2013, a method for quantitatively calculating the similarity of an X matrix and a Y matrix is still lacked, which greatly limits the practical application of the runoff frequency spectrum. The runoff frequency spectrum similarity calculation becomes an unsolved technical problem.

Disclosure of Invention

Aiming at the defects, the invention provides a method for directly calculating the similarity of the runoff frequency spectrum data matrix without calculating the graph similarity, which is used for quantifying the sponge effect.

The invention provides the following technical scheme: a runoff frequency spectrum similarity calculation method for quantifying a sponge effect comprises the following steps:

s1: acquiring runoff daily value data of a long-time sequence to generate a runoff frequency spectrum matrix

S2: generating a digitized runoff frequency matrix representing the natural landform and the sponge city respectively: drawing a runoff frequency spectrogram by an X matrix and a Y matrix, wherein the similarity of the X matrix and the Y matrix represents the natural runoff characteristic restoration degree;

s3: calculating runoff frequency spectrum similarity:

s31: representing the graphical runoff spectrum by the digitized runoff frequency matrix:

wherein X is an n row 2 column matrix and Y is an m row 2 column matrix;andis from big to smallThe unit of the sequenced runoff is mm/d; i/T represents the cumulative frequency and the radial flow x_iAnd y_iThe frequency location of the location; n and m represent total runoff event occurrence days in units of d; t is the number of statistical years and has the unit of y; the n/T and the m/T are maximum cumulative frequencies and represent matrix lengths;

s32: moving the traffic with different accumulated frequencies in the X matrix and the Y matrix to the nearest frequency position to align the accumulated frequencies of the X matrix and the Y matrix;

s33: comparing the aligned X matrix with the aligned Y matrix, wherein the runoff quantity of the X matrix and the runoff quantity of the Y matrix corresponding to the same frequency position are called as comparison, and directly calculating the comparison difference of each group;

s34: and calculating the similarity of the aligned X matrix and Y matrix according to the comparable difference and the water quantity weight of each group, wherein the similarity represents the natural runoff characteristic restoration degree.

Further, the runoff is the runoff outside the earth surface of a research site, is obtained through on-line monitoring and model simulation, and is carried out according to the requirements in the sponge city construction evaluation standard GB/T51345-2018.

Further, the step of S2 includes the steps of:

s21: the daily runoff value obtained by on-line monitoring and simulation using a model is usually m³D, recorded, divided by the area of the field to give units mm/d; considering that the recording precision of rainfall is 0.1mm/d, further rounding off the radial flow to take 1-digit effective number after decimal point, and making the unit and precision of the radial flow consistent with the unit and precision of the rainfall;

s22: drawing a runoff frequency spectrum: and sequencing all the runoff quantities from large to small, counting the cumulative occurrence times of a certain runoff quantity, and dividing the cumulative occurrence times by the years of a counting time interval to obtain the cumulative frequency. And drawing by taking the runoff as an abscissa and the cumulative frequency as an ordinate to obtain a runoff spectrogram.

The X matrix and the Y matrix respectively represent a natural landform and a runoff frequency spectrum of a sponge city, and the similarity of the X matrix and the Y matrix is the natural runoff characteristic restoration degree and is used for quantifying the sponge effect.

Further, in the step S22, when plotting the cumulative frequency as the ordinate, in order to highlight the large runoff events, the logarithmic coordinate is used as the ordinate.

Further, the step of S32 includes the steps of:

s321: aligning the Y matrix to the X matrix: sequentially searching each frequency in the Y matrix to be equal to or smaller than the maximum value thereof in the X matrix as a frequency position to be aligned; merging the traffic to be aligned to the same frequency position into a new value by the following method:

the number of days of occurrence of the new traffic equals the sum of the number of days of occurrence of the combined traffic, i.e., ∑ (y)_iNumber of days of onset + y_i+1Days of occurrence + …); after the treatment, the total runoff and the total occurrence days of Y are kept unchanged;

s322: the method of step S321 is adopted to align the X-aligned Y.

Further, the calculation formula of the comparable difference degree of each group in the step S33 is as follows:

absolute degree of difference ═ y_i/T-x_i/T|

Relative degree of difference ═ y_i/T-x_i/T|/x_i/T。

Further, in the step S34, a calculation formula for calculating the similarity between the aligned X matrix and the aligned Y matrix according to the comparable difference and the water amount weight of each group is as follows:

similarity is 1-sigma (relative difference degree)₁Water flow weight₁+ … + relative degree of difference_iWater flow weight_i+ … + relative degree of difference_nWater flow weight_n)

The runoff frequency spectrum matrix similarity is obtained through calculation of the formula; the closer the similarity is to 1, the more similar the two radial flow spectrum matrixes are, and the two matrixes are completely the same if the similarity is equal to 1; the X matrix represents a natural landform and is a reference matrix, and the Y matrix represents a sponge city and is a matrix to be compared; if more than 1 matrix is to be compared, e.g., multiple development scenarios are available in the same site, the X matrix must be the longest matrix length.

Further, the water weight is calculated according to the aligned X, and the water weight that the ith group can compare is calculated as follows:

water volume weight_iRepresenting the proportion of the runoff at frequency position i/T in the total runoff, which determines the contribution of each alignable matrix discrepancy

Further, the above algorithm is implemented by Microsoft Excel or programming language.

Further, the obtained runoff frequency spectrum is used for evaluating the construction effect or optimizing an engineering scheme.

The invention has the beneficial effects that:

1. the runoff frequency spectrum similarity calculation method for quantifying the sponge effect provided by the invention expresses the graphical runoff frequency spectrum by using the digital runoff data matrix, thereby realizing the purpose of directly calculating the similarity of the data matrix without calculating the graphical similarity.

2. The runoff frequency spectrum similarity calculation method for quantifying the sponge effect provided by the invention moves the flow with different accumulated frequencies of the X matrix and the Y matrix to the nearest frequency position, aligns the accumulated frequencies of the X matrix and the Y matrix, and then calculates the similarity of the aligned X matrix and Y matrix.

3. The runoff frequency spectrum obtained by calculation through the runoff frequency spectrum similarity calculation method for quantifying the sponge effect can be used for construction effect evaluation and engineering scheme optimization. When the method is used for optimizing the engineering scheme, different development schemes can be designed for a construction site, the restoration degree of the natural runoff characteristics by the different development schemes is calculated respectively, and the optimal engineering scheme is determined according to the principle of restoring the natural runoff characteristics to the maximum degree under the condition of technical economy and feasibility.

Drawings

The invention will be described in more detail hereinafter on the basis of embodiments and with reference to the accompanying drawings. Wherein:

FIG. 1 is a flow chart of a runoff spectrum similarity calculation method for quantifying the sponge effect according to the present invention;

FIG. 2 is a diagram of the operation of Microsoft Excel-based runoff spectrum analysis in example 2 of the present invention;

FIG. 3 is a diagram of a first operation procedure of aligning a Y matrix to an X matrix in embodiment 2 of the present invention;

FIG. 4 is a diagram illustrating a second operation procedure of aligning the Y matrix to the X matrix in embodiment 2 of the present invention;

FIG. 5 is a route diagram of a rainwater collection and utilization technique according to example 3 of the present invention;

FIG. 6 is a graph of the results of example 3 of the present invention for generating runoff spectra at different volumes and their similarity to the grass runoff spectra;

fig. 7 is a runoff spectrum similarity result graph after the development and construction of embodiment 3 of the present invention;

fig. 8 is a drawing as described in the background of the invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Example 1

As shown in fig. 1, a runoff spectrum similarity calculation method for quantifying the sponge effect is provided for the present implementation, and includes the following steps:

s1: acquiring runoff daily value data of a long-time sequence, wherein the runoff refers to the runoff outside the earth surface of a research site, is obtained through online monitoring and model simulation, and is carried out according to the requirements in the sponge city construction evaluation standard GB/T51345-2018;

s2: generating a runoff frequency spectrum diagram with an X matrix and a Y matrix which respectively represent a natural landform and a sponge city, wherein the similarity of the X matrix and the Y matrix is the runoff frequency spectrum of the natural runoff feature restoration degree:

specifically, S21: the daily runoff value obtained by on-line monitoring and simulation using a model is usually m³D, recorded, divided by the area of the field to give units mm/d; considering that the recording precision of rainfall is 0.1mm/d, further rounding off the radial flow to take 1-digit effective number after decimal point, and making the unit and precision of the radial flow consistent with the unit and precision of the rainfall;

s22: drawing a runoff frequency spectrum: and sequencing all the runoff quantities from large to small, counting the cumulative occurrence times of a certain runoff quantity, and dividing the cumulative occurrence times by the years of a counting time interval to obtain the cumulative frequency. Drawing by taking the runoff as an abscissa and the accumulated frequency as an ordinate to obtain a runoff frequency spectrum; further, when plotted with cumulative frequency as the ordinate, logarithmic coordinates are used as the ordinate) to highlight large runoff events.

The X matrix and the Y matrix respectively represent a natural landform and a runoff frequency spectrum of a sponge city, and the similarity of the X matrix and the Y matrix is the natural runoff characteristic restoration degree and can be used for quantifying the sponge effect;

s3: calculating runoff frequency spectrum similarity:

s31: and representing the graphical runoff spectrum by a digitized runoff spectrum matrix:

wherein X is an n row 2 column matrix and Y is an m row 2 column matrix;andthe runoff is sorted from large to small, and the unit is mm/d; i/T represents the cumulative frequency and the radial flow x_iAnd y_iThe frequency location of the location; n and m represent total runoff event occurrence days in units of d; t is the number of statistical years and has the unit of y; the n/T and the m/T are maximum cumulative frequencies and represent matrix lengths;

after the runoff frequency spectrum is represented by the runoff frequency spectrum matrix, the runoff frequency spectrum similarity is solved. The difficulty is that the accumulated frequencies corresponding to the runoff quantities in the X matrix and the Y matrix are different, and direct comparison cannot be performed;

s32: moving the traffic with different accumulation frequencies in the X matrix and the Y matrix to the nearest frequency position to align the accumulation frequencies of the X matrix and the Y matrix: the method specifically comprises the following steps:

s321: aligning the Y matrix to the X matrix: sequentially searching each frequency in the Y matrix to be equal to or less than the maximum value thereof in the X matrix as a frequency position to be aligned; merging the traffic to be aligned to the same frequency position into a new value by the following method:

the number of days of occurrence of the new traffic equals the sum of the number of days of occurrence of the combined traffic, i.e., ∑ (y)_iNumber of days of onset + y_i+1Days of occurrence + …); after the processing, the total runoff and the total occurrence days of the Y matrix are kept unchanged;

s322: the method of step S321 is adopted to align the X-aligned Y, and after step S321, all frequencies in the aligned Y matrix can be found in the X matrix, but there may be "redundant" frequencies in the X matrix that are not aligned. Thus, the X matrix is aligned to the aligned Y matrix. The X matrix is longer than the Y matrix, dividing X into a first half and a second half. The first half is a part as long as the Y matrix after alignment, and the frequency alignment process is performed by the same method as before.

The second half is the portion of the X matrix that exceeds the length of the aligned Y matrix. This portion of the runoff volume and its cumulative frequency are directly preserved. These frequencies can be considered to be present in the aligned Y matrix, except that they are zero for the amount of runoff. After the processing, the total runoff and the total occurrence days of the X matrix are also kept unchanged;

s33: comparing the aligned X matrix with the aligned Y matrix, wherein the runoff quantity of the X matrix and the runoff quantity of the Y matrix corresponding to the same frequency position are called as comparison, and calculating the comparison difference of each group:

absolute degree of difference ═ y_i/T-x_i/T|

Relative degree of difference ═ y_i/T-x_i/T|/x_i/T；

S34: calculating the similarity of the aligned X matrix and Y matrix according to the contrastive difference and the water quantity weight of each group, and further obtaining the runoff frequency spectrum of the nature runoff feature restoration degree, wherein the similarity calculation formula of the aligned X matrix and Y matrix is as follows:

similarity is 1-sigma (relative difference degree)₁Water flow weight₁+ … + relative degree of difference_iWater flow weight_i+ … + relative degree of difference_nWater flow weight_n)

The runoff frequency spectrum matrix similarity is obtained through calculation of the formula; the closer the similarity is to 1, the more similar the two radial flow spectrum matrixes are, and the two matrixes are completely the same if the similarity is equal to 1; the runoff frequency spectrum matrix is a digital expression mode of the runoff frequency spectrum, so the similarity of the runoff frequency spectrum matrix is equal to the similarity of the runoff frequency spectrum; the X matrix represents that the natural landform is a reference matrix, and the Y matrix represents that the sponge city is a matrix to be compared; if more than 1 matrix is to be compared, e.g., multiple development plans are in the same site, then the X matrix must be the longest in matrix length. This is because calculating the relative difference requires the value in the X matrix as the denominator, and the water amount weight is also calculated based on the X matrix. Only if the X matrix is the longest matrix, the denominator of the calculated relative difference degree is more than 0, and the weights of all frequency positions in all matrixes to be compared are the same, so that the similarity of all matrixes to be compared to the reference matrix is ensured to have comparability;

the runoff frequency spectrum can be evaluated by a construction effect and can also be used for optimizing an engineering scheme. When the method is used for optimizing the engineering scheme, different development schemes can be designed for a construction site, the restoration degree of the natural runoff characteristics by the different development schemes is calculated respectively, and the optimal engineering scheme is determined according to the principle of restoring the natural runoff characteristics to the maximum degree under the condition of technical economy and feasibility.

The water quantity weight is calculated according to the aligned X matrix, and the water quantity weight which can be compared in the ith group is calculated as follows:

water volume weight_iWhich represents the proportion of the runoff at frequency location i/T in the total runoff and determines the contribution of each alignable matrix discrepancy.

The algorithm provided by the embodiment can be realized by Microsoft Excel or programming language, and the obtained runoff spectrum of the natural runoff feature restoration degree is used for evaluating the construction effect or optimizing the engineering scheme. When the method is used for optimizing the engineering scheme, different development schemes can be designed for a construction site, the restoration degree of the natural runoff characteristics by the different development schemes is calculated respectively, and the optimal engineering scheme is determined according to the principle of restoring the natural runoff characteristics to the maximum degree under the condition of technical economy and feasibility.

Example 2

A runoff spectroscopy tool based on Microsoft Excel.

A radial flow spectroscopy tool was developed using Microsoft Excel, which included two parts: (1) a radial flow spectrum generation tool, and (2) a radial flow spectrum similarity calculation tool.

Taking two groups of day-by-day flow data of 27 years as an example, the development and application of the tool are explained. Each group 9862Data in m³And/d, which represent natural features and sponge cities, respectively.

Part (1): a runoff spectrum generation tool.

A set of 27 year runoff data representing a sponge city was pasted in Microsoft Excel and sorted in descending order with the "sort" on the "data" tab. After sorting is complete, they are sorted from large to small, with 456 values greater than 0.

As shown in FIG. 2, the 456 data items sorted from large to small are pasted in column A, which is located at A5: A460. The flow rate units are then converted to mm/d and are shown in column B.

The flow data in mm/d were 1 decimal and the results are shown in column C. The execution was performed using Microsoft Excel self-contained functions. After taking the 1-bit decimal, the last row C460 is 0.0, and this row is deleted. Therefore, the valid data is C5: C459.

Duplicate values in the valid data are removed and the results are shown in column D. The execution was performed using Microsoft Excel self-contained functions. For example, when the function is executed in the cell D79, if the number of cells equal to C79 in the region C5: C79 > is 2, the "/" symbol is input, or else equal to C79.

The number of days of reoccurrence of the same flow was counted and the results are shown in column E. The execution was performed using Microsoft Excel self-contained functions. For example, when the function is executed in the E79 cell, if the number of cells in C5: C459 is equal to the number >0 of cells in D79, the number of cells in D79 is input; otherwise, a "/" symbol is entered.

The "/" symbol is removed. The values of D5: E459 are selectively pasted to H5: I459, and the column 187 with the "/" symbol. The "delete duplicate" is performed in the "data" tab, the duplicate 186 lines "/" are deleted, only the first occurrence of "/" from top to bottom is retained, moving the data below it up one line to cover this line. Thus the 187 row "/" symbol is deleted leaving only H5: H272 with data.

Statistics for cumulative counts greater than or equal to a certain runoff over days occurred are shown in column J.

The cumulative frequency corresponding to the runoff was calculated and the results are listed in column G. For example, the cumulative frequency of H78 is obtained by inputting the formula J78/year of analysis, here 27 years, in G78 cells.

And drawing a runoff frequency spectrum. Through the above operations, G5: H272 is a radial flow spectrum and is marked as a Y matrix.

And performing the same operation on the other group of data representing the natural landform to obtain a lawn runoff frequency spectrum which is recorded as an X matrix.

The runoff rate daily value is taken as an abscissa, the accumulated frequency is taken as an ordinate, a scatter plot is drawn, and the obtained runoff spectrum is shown in fig. 6.

Part (2): and a runoff frequency spectrum similarity calculation tool.

The part (2) is divided into 3 sub-parts: (1) aligning the Y matrix to the X matrix; (2) aligning the X matrix to the aligned Y matrix; (3) and calculating the runoff frequency spectrum similarity of the aligned X matrix and Y matrix.

The following are described respectively:

(1) the Y matrix is aligned to the X matrix.

As shown in fig. 3-4, the X matrix is attached to a9: C230 and the Y matrix is attached to D9: F276, with parameters including runoff volume, days of occurrence, and cumulative frequency. The number of days of occurrence of the same runoff volume may be more than 1 day, but the runoff volume and the accumulation frequency are not repeated, and each runoff volume corresponds to an accumulation frequency which represents the recurrence frequency of runoff events greater than or equal to the runoff volume.

And sequentially searching the frequency position to be aligned with each frequency in the Y matrix by taking the X matrix as a search range, and listing the result in the H column. The execution was performed using Microsoft Excel self-contained functions. For example, when the H112 cell executes the function, the maximum value less than or equal to F112 is first searched in C9: C800, and then the value is located and input to the H112 cell. As shown in fig. 3-4, 4.556, 4.630, 4.667, and 4.852 in column H have equal values in column C, and the positions to be aligned are themselves; 4.593 in column H has no equivalent value in column C, and the closest frequency to it is 4.556; 4.704 and 4.741 in column H have no equivalent value in column C, and the closest frequencies to them are both 4.667. After this search, different flow values in the Y matrix may be aligned to the same frequency position, and thus the frequency positions to be aligned in the H column are repeated.

The repeat values in column H are removed and the results are shown in column J. The execution was performed using Microsoft Excel self-contained functions. For example, when the function is executed in J112 cells, if H9: H112 equals the number of cells in H112 >1, the "/" symbol is entered; otherwise, H112 is input.

The number of flows to be aligned to the same frequency location is counted and the results are listed in column I. The execution was performed using Microsoft Excel self-contained functions. For example, when the I112 cell executes the function, the number of traffic to be aligned to J112 is counted.

The new flux aligned to each frequency position in column J is calculated and the results are listed in column K. Calculated by weighted average, performed with Microsoft Excel self-contained function. Such as when the K112 cell executes the function, a new flow will be calculated that is aligned to the frequency location of J112.

The number of days of occurrence for each new flow value is counted and the results are shown in column L. The execution was performed using Microsoft Excel self-contained functions. For example, when the function is executed in L112 units, the number of days of occurrence of the K112 flow rate is calculated.

And generating an aligned runoff spectrum Y matrix. Data of J9: K276 is pasted to M9: N276 by selective pasting, "delete duplicate item" is executed in the "data" tab, duplicate "/" is deleted, only the "/" appearing first from top to bottom is retained, and the data below it is moved up one line to cover the line. The "/" symbol is then removed, leaving only M9: N184 with more data.

And calculating the occurrence days of each runoff quantity on the aligned runoff spectrum Y matrix, and listing the result in a column O. The execution was performed using Microsoft Excel self-contained functions. For example, when the O112 cell executes the function, the equal value of N112 in J9: J800 is searched, and then the position of the value corresponding to L9: L $800 is found and input into O112.

At this point, the process of aligning the Y matrix to the X matrix is complete.

And finally, checking. The initial radial flow spectrum Y is located at D9: F276, and the aligned radial flow spectrum is located at M9: O184. The execution was performed using Microsoft Excel self-contained functions. When the M6 cell executes the function, whether the total days before and after the data processing are consistent or not is checked, and if the total days are consistent, the input is correct. When the O6 cell executes the function, whether the total flow rate is consistent before and after the data processing is checked, and if the total flow rate is consistent, the input is correct.

When the test is correct, M9: O184 is the aligned runoff spectrum Y, and the parameters comprise runoff volume, occurrence days and accumulation frequency.

(2) The X matrix is aligned to the aligned Y matrix.

All frequencies in the aligned Y matrix can be found in the X matrix, but there may also be "redundant" frequencies in the X matrix that are not present in the aligned Y matrix. Therefore, it is also necessary to align the X matrix to the aligned Y matrix.

The alignment process is performed in S-W columns, and the alignment method is divided into an upper half and a lower half. The alignment method of the upper half is the same as the alignment method of the Y matrix in the H-L columns. The end position of the upper half is automatically found by the Microsoft Excel self-contained function. In the R column drag function, Microsoft Excel automatically finds the first value in the X matrix that exceeds the Y matrix and inputs this value to the corresponding position in the R column. In this example, Microsoft Excel enters the first value in the X matrix that exceeds the Y matrix into the R210 cell, from which the bottom half begins.

The value of the lower half of U-W is equal to the original value in the X matrix, which is equivalent to direct reservation. These directly reserved frequency positions can be considered to exist in the aligned Y matrix, except that the amount of radial flow corresponding to these frequency positions in the Y matrix is zero.

Next, an aligned radial flow spectrum X matrix is generated. Data of U9: V230 is pasted to X9: Y230 by selective pasting, "delete duplicate" is executed in the "data" tab, duplicate "/" is deleted, only the "/" appearing first from top to bottom is retained, and the data below it is moved up one line to cover this line. The "/" symbol is then removed, leaving only X9: Y205 with more data.

And calculating the occurrence days of each runoff volume on the aligned runoff spectrum X matrix, and checking the total days and the total runoff volume, wherein the calculation and checking method is the same as the method for aligning the Y matrix in the M-O column.

When the test is correct, X9: Z205 is a radial flow spectrum X matrix after alignment, and parameters comprise radial flow, occurrence days and cumulative frequency.

The frequency position and the matrix length of the X matrix and the Y matrix after alignment are the same. The runoff quantity corresponding to the same frequency position is called as a comparison, and the size can be directly compared.

(3) And calculating the runoff frequency spectrum similarity of the aligned X matrix and Y matrix.

The calculation of the runoff spectrum similarity is completed at AB9 AE 205.

The absolute difference was calculated and the results are shown in column AB. For example, ABs (Y9-N9) is input to AB9 cell, which indicates that the absolute difference between Y112 and N112 is calculated.

The relative degree of difference was calculated and the results are shown in the AC column. For example, at the AC9 cell input AB9/Y9, the relative difference with respect to the X matrix can be found.

The water weight was calculated and the results are listed in the AD column. The execution was performed using Microsoft Excel self-contained functions. For example, when the AD9 cell executes the function, the proportion of the flow corresponding to the frequency of 0.037d/y in the total flow is calculated.

The weighted relative difference was calculated and the results are listed in AE. For example, the AE cell input is AC9 AD9, and the weighted relative difference is obtained.

And finally calculating the runoff frequency spectrum similarity. The cell of AD7 is input with 1-SUM (AE9: AE800), where SUM (AE9: AE800) represents the SUM of weighted relative differences, and the similarity is obtained by subtracting it from 1.

In this example, the radial flow spectrum similarity of the X matrix and the Y matrix is 0.52.

Example 3

A roof area 5500m is constructed in a certain place²According to the traditional method, roof rainwater is directly discharged to the outside of the site after being collected. The rainwater collection and utilization is adopted to reduce the amount of discharged rainwater, the lawn is used as a natural contrast to evaluate the restoration effect of the rainwater collection and utilization on the natural runoff characteristics, and an optimal engineering scheme is found.

The rainwater collection and utilization technical route is shown in fig. 5. Because the runoff of the roof in the early stage of rainfall is dirty, the runoff of 3mm on the roof in the early stage of rainfall is abandoned through the abandoning device, and the rainwater in the later stage is collected and stored cleanlyThe water storage device is stored in a rainwater storage tank and is used for ground watering and greening watering, and the ground area and the greening area are twice of the roof area. The ground is sprinkled 2 times per month, and the water consumption is 2L/m²Once per time. Automatic irrigation is adopted for greening, when the evaporation capacity is larger than the precipitation capacity, the evaporation capacity is replenished by irrigation, so the greening irrigation capacity is dynamically changed, rainwater which cannot be stored is discharged outside by an overflow pipe, and the part is the runoff of the actual roof discharged to the outside of the field. Therefore, rainwater is collected and utilized, the outward radial flow can be reduced, and the effect of restoring the natural radial flow characteristics is achieved.

A first link: and acquiring runoff data.

A roof rainwater collection and utilization water balance estimation model is established by using Microsoft Excel, the volume of a rainwater storage pool is input, and continuous calculation is carried out day by using the model based on the historical daily rainfall and evaporation records of 27 local years (except 1991 and 2018, 2013) to obtain the daily discharge runoff of the rainwater storage pool under the 27-year calendar historical meteorological record.

Meanwhile, a grassland runoff estimation model is established by using Microsoft Excel, and continuous day-by-day calculation is carried out based on the same historical meteorological record to obtain the grassland runoff discharged day-by-day under the 27-year calendar historical meteorological record.

And a second link: generating radial flow spectra

The runoff spectra were generated using the Microsoft Excel runoff spectroscopy tool established in examples 1 and 2.

And a third step: calculating runoff frequency spectrum similarity

The runoff spectrum similarity of rain collection and turf was calculated using the Microsoft Excel runoff spectrum analysis tool established in examples 1 and 2.

And a fourth step of: optimizing the engineering scheme.

Changing the volume of the rainwater storage pool, repeating the calculation of the three steps to generate runoff frequency spectrums with different volumes and the similarity between the runoff frequency spectrums and the runoff frequency spectrums of the grass land. The results are shown in FIG. 6. In the figure, the maximum runoff of the grass is 147.2mm/d, corresponding to a cumulative frequency of 0.037 d/y; the minimum runoff was 0.1mm/d, corresponding to a total cumulative frequency (i.e. matrix length) of 32.59 d/y.

The maximum runoff of the roof is 189.2mm/d, and the corresponding cumulative frequency is 0.037 d/y; the minimum runoff was 0.1mm/d, corresponding to a total cumulative frequency of 85.15 d/y. After the grassland is built into a roof, the rainfall runoff and the occurrence frequency of runoff events are greatly increased.

After rainwater is collected and utilized, roof runoff frequency spectrums are shifted to the left and simultaneously shortened, and the outward runoff quantity is reduced and the frequency is reduced. For convenience of description, the frequency of less than or equal to 0.3d/y is called low frequency, 0.3-6 d/y is called medium frequency, and more than or equal to 6d/y is called high frequency. When the volume of the water storage tank is smaller (47 m)³) The matrix length is close to grass, but the runoff is still greater than grass. When the storage tank volume is appropriate (238 m)³) The high-frequency runoff is obviously reduced, and the medium-frequency runoff is close to the grassland. When the volume of the water storage tank is larger (598 m)³) The high-frequency runoff completely disappears, the medium-frequency runoff is smaller than the grassland, and the low-frequency runoff is close to the grassland. When the volume of the water storage tank is overlarge (801 m)³) Runoff of almost all frequencies is less than grassland, indicating excess rainwater collection and insufficient surface runoff drainage compared to natural landscapes.

The runoff spectrum similarity after development and construction is calculated according to the natural landform vs. in fig. 6, and the restoration degree of the rainwater collection on the natural runoff characteristics can be evaluated, as shown in fig. 7, which includes but is not limited to the volume of the rainwater storage pool in fig. 6.

In fig. 7, the runoff total amount similarity refers to the similarity between the total runoff amount discharged outside the rainwater storage tank and the total runoff amount of the grass land. This is a similar indicator to the annual runoff yield control rate. Along with the increase of the volume of the rainwater storage tank, the similarity of the total runoff amount is also increased, and the maximum value reaches 1; the volume of the rainwater storage pool is continuously increased, and the similarity of the total runoff amount is reduced. This figure illustrates that there are always 1 reservoir volume that can make the total runoff volume for both the grass and rain reservoirs the same, or the total runoff volume control rate the same. Therefore, if the annual runoff total control rate is used for evaluating the natural runoff characteristic restoration degree, the complete restoration conclusion can be drawn.

And the maximum value of the runoff frequency spectrum similarity is 0.66 by adopting the runoff frequency spectrum for evaluation, which shows that the maximum restoration degree of the roof rainwater collection on the natural runoff characteristics is only 0.66 if the comparison is carried out on the time resolution of the day. Furthermore, a platform with runoff spectrum similarity equal to 0.66 is a platform, that is, the rainwater storage capacity that can achieve maximum remediation is not a value, but a range. As shown in fig. 6, the control effect of rainwater collection on roof runoff with different intensity is different, and the maximum restoration is the best balance for the different effects, and the best balance can be realized within a certain range, and the minimum value in the volume range has the best technical economy and is therefore the best scheme.

The above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.

Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims above, any of the claimed embodiments may be used in any combination. The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.