Method for calculating extreme value of substance flux of river

Abstract

The invention discloses a river substance flux extreme value calculation method, which belongs to the technical field of hydrology and water quality measurement and calculation, and comprises the following steps: S1, obtaining flow data and substance concentration data of a certain section of a river; s2, according to the flow data and the substance concentration data, constructing a river flow flux calculation model, and calculating the day-by-day substance flux of the river; s3, calculating an extreme threshold index according to the river day-by-day substance flux; s4, according to the day-by-day substance flux and the extreme threshold index, obtaining river day-by-day substance flux sequences under different extreme grades; s5, according to the river day-by-day substance flux sequence, values in the sequence are summed, and therefore river substance flux extreme values of different grades are obtained.The river substance flux extreme value calculation method is obtained on the basis of the continuous process and frequency distribution of river flux changes, complete hydrology and water quality change events are reflected, and the calculation accuracy of the river substance flux extreme values is improved. And the consistency of the river substance flux extreme value and the actual hydrological change process is improved.

Description

Technical Field

[0001] The present invention relates to the technical fields of hydrology and water quality measurement, and particularly relates to a method for calculating extreme values of river material fluxes. Background Art

[0002] Changes in material fluxes in rivers (such as nitrogen and phosphorus) are important reasons for the deterioration of downstream water quality, the loss of biodiversity, and eutrophication. With the interaction between human activities and governance measures, significant changes in material fluxes have occurred in many rivers globally. Since river material fluxes are controlled by multiple factors, such as dam construction, climate change, nutrient legacy, and land use, the material fluxes in rivers have significant variability. Exploring the spatio-temporal characteristics of river material flux changes helps to deeply understand the mechanisms controlling river ecosystem changes. With the frequent occurrence of climate extreme events, significant material load outputs have occurred in many river basins globally in a short period of time. Driven by heavy rainfall or drought, extreme material outputs from rivers may become a common phenomenon in many large rivers.

[0003] However, current research mainly focuses on the total fluxes or their structures of substances such as nitrogen and phosphorus in rivers, ignoring the different components of these fluxes and their driving mechanisms. Affected by the intensification of climate change, the frequency of extreme hydrological events in rivers is increasing continuously, leading to an intensified output of material fluxes such as nutrients to receiving water bodies, which has become an important environmental problem in river environmental research. Current research on river material fluxes mainly focuses on fluxes exceeding or below a certain percentile threshold, ignoring the complete spectrum of load changes. Summary of the Invention

[0004] To solve the above problems, the present invention provides a method for calculating extreme values of river material fluxes, and the present invention is implemented through the following technical solutions.

[0005] A method for calculating extreme values of river material fluxes includes the following steps:

[0006] S1, obtaining flow data and substance concentration data of a certain cross-section of a river, where the time resolution of the flow data is not lower than the daily scale;

[0007] S2, constructing a river flux calculation model according to the flow data and substance concentration data obtained in step S1, and calculating the daily river material fluxes;

[0008] S3, calculating extreme threshold indicators according to the daily river material fluxes, where the extreme threshold indicators include the threshold of extreme material fluxes and the daily change rate of fluxes;

[0009] S4, obtaining the daily river material flux sequences under different extreme levels according to the daily material fluxes and extreme threshold indicators;

[0010] S5. Based on the daily material flux sequence of the river, sum the values in the sequence to obtain the extreme values of the river material flux at different levels.

[0011] Preferably, in step S1, the flow data is continuous flow observation data at daily or sub - daily scale, and the sequence length is not shorter than 1 hydrological year; the material concentration data is the mass of a certain substance in the unit volume of water.

[0012] Preferably, in step S2, it includes the following sub - steps:

[0013] S21. Construct a river flux calculation model:

[0014] Input the flow data and the material concentration data into the LOADEST model, select the maximum likelihood method to estimate the flux, calculate the Akaike Information Criterion AIC and Schwarz Information Criterion SPPC of different equations, and select the equation with the lowest AIC and the largest SPPC as the river flux calculation model. The fitting equation of the model is as follows:

[0015] ln(L) = a 0 +a 1 LQ + a 2 Sin(2πD)+a 3 Cos(2πD)+a 4 D

[0016] Where,

[0017] LQ = L(Q)-Center(Q)

[0018] D = DT - Center(DT)

[0019]

[0020] In the formula, L is the daily flux of the substance (kg / d); LQ is the difference between the logarithm of the flow and the logarithm of the central value of the flow; D is the difference between the date and the central value of the date; Sin and Cos are the sine and cosine functions respectively; Center(X) is the central value of X; is the average value of X; n is the sequence length of X; a 0 ~a 4 are the fitting coefficients of the equation;

[0021] S22. Determine the fitting coefficients.

[0022] Preferably, in step S3, the calculation formulas for the threshold of the extreme material flux and the daily change rate of the flux are as follows:

[0023] TL j =PERC(DL i ,PT j )

[0024]

[0025] In the formula, TL is the threshold of the extreme substance flux; DL is the daily substance flux; PT is the percentile; LC is the daily change rate of the flux; i and j are the date and the extreme flux level respectively.

[0026] Preferably, in the step S4, the extreme flux levels include extreme high flux and extreme low flux:

[0027] For the extreme high flux sequence, the sequence is the flux record exceeding the TL threshold, which starts when LC is higher than the threshold of the daily change rate of the flux and ends when LC is lower than the threshold of the decline of the daily change rate of the flux;

[0028] For the extreme low flux sequence, the sequence is the flux record where DL is less than the threshold specified by TL.

[0029] Preferably, in the step S5, the calculation formula for the extreme values of the river substance flux of different types of levels is as follows:

[0030]

[0031] In the formula, RFC j is the extreme value of the river substance flux of level j; DL is the daily substance flux; js and je are the start and end dates of the jth flux extreme value respectively.

[0032] The beneficial effects of the present invention are as follows:

[0033] According to the continuous river flow data and discrete water quality monitoring data of the present application, a continuous sequence sample of daily substance flux events can be obtained. Compared with the daily flux sample obtained from a single discrete monitoring value, the number of samples is larger, and the hydrological process that can be reflected is more comprehensive. The proposed method has strong applicability in the basins with conventional hydrological and water quality observations.

[0034] The present application comprehensively uses two indicators of frequency and rate as the basis for distinguishing extreme variables from conventional variables. The extracted extreme flux samples are continuous, realizing the continuous distribution of river substance flux samples in time and improving the consistency between the extreme flux process and the hydrological extreme process. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the present invention, the drawings required for use in the following description of the specific embodiments will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0036] Figure 1 : Flow chart of a method for calculating extreme values of river material flux according to the present invention;

[0037] Figure 2 : Schematic diagram of extreme values of river flux;

[0038] Figure 3 : Chart of calculation results of daily total nitrogen flux;

[0039] Figure 4 : Chart of calculation results of extreme high and low flux sequence values of total nitrogen;

[0040] Figure 5 : Chart of recognition results of extreme high values of material flux;

[0041] Figure 6 : Chart of recognition results of extreme low values of material flux; Detailed implementation manners

[0042] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0043] A method for calculating extreme values of river material flux, as Figure 1 shown, includes the following steps:

[0044] S1. Obtain the flow rate data and material concentration data of a certain cross-section of the river, where the time resolution of the flow rate data is not lower than the daily scale.

[0045] The flow rate data is continuous flow rate observation data on a daily or sub-daily scale, and the sequence length is not shorter than 1 hydrological year; the material concentration data is the mass of a certain substance in the water volume per unit volume.

[0046] Specifically, an example of the present invention is a certain cross-section of River A, which has flow rate monitoring data and synchronous total nitrogen monitoring data. Among them, the flow rate data is a daily continuous value, and the time span is from 2007 to 2015; the total nitrogen monitoring data is monthly data from 2007 to 2015. The specific data is shown in Table 1.

[0047] Table 1 Flow rate and nitrogen concentration data of a certain cross-section of River A

[0048] Date <![CDATA[Flow rate (m 3 / s)]]> Total Nitrogen (mg / L) 2007 / 1 / 1 4250 1.917 2007 / 1 / 2 4260 - 2007 / 1 / 3 4200 - 2007 / 1 / 4 4210 - …… …… …… 2015 / 12 / 1 6280 1.32 …… …… ……

[0049] S2. According to the flow rate data and material concentration data obtained in step S1, construct a river flux calculation model to calculate the daily river material flux.

[0050] Input the flow rate data and substance concentration data into the LOADEST model, select the optimal flux calculation model, and calibrate the model parameters, including the following sub-steps:

[0051] S21, construct a river flux calculation model:

[0052] Input the flow rate data and substance concentration data into the LOADEST model, select the maximum likelihood method to estimate the flux, calculate the Akaike Information Criterion (AIC) and Schwarz Information Criterion (SPPC) of different equations, and select the equation with the lowest AIC and the largest SPPC as the river flux calculation model. Table 2 shows the two indicators of different daily total nitrogen flux fitting equations. According to the screening principle, Model 7 is the optimal model.

[0053] Table 2 Evaluation index values of different models based on AMLE

[0054]

[0055]

[0056] The fitting equation of the model is as follows:

[0057] ln(L) = a 0 + a 1 LQ + a 2 Sin(2πD) + a 3 Cos(2πD) + a 4 D

[0058] Where,

[0059] LQ = L(Q) - Center(Q)

[0060] D = DT - Center(DT)

[0061]

[0062] In the formula, L is the daily flux of the substance (kg / d); LQ is the difference between the logarithm of the flow rate and the logarithm of the central value of the flow rate; D is the difference between the date and the central value of the date; Sin and Cos are the sine and cosine functions respectively; Center(X) is the central value of X; is the average value of X; n is the sequence length of X; a 0 ~a 4 are the fitting coefficients of the equation.

[0063] Calculated according to the above formula, the central value of the flow rate is 12.9509, and the central value of the date is 2011.663.

[0064] S22, determine the fitting coefficients.

[0065] According to the optimal model, the fitting parameters of the fitting equation are calibrated. The determination coefficient R2 of the fitting equation reaches 0.9034, and the residual is 0.0422. The fitting effect is good, and the fitting coefficients are shown in Table 3.

[0066] Table 3 Fitting Coefficients of the Fitting Equation

[0067] Parameter Name <![CDATA[a 0 > <![CDATA[a 1 > <![CDATA[a 2 > <![CDATA[a 3 > <![CDATA[a 4 <!-- 4 -->]]> Fitted Value 14.2831 1.0467 -0.0809 -0.0738 -0.0213

[0068] According to the obtained formula and parameters, the daily total nitrogen flux of the cross-section can be calculated, and the results are as attached Figure 3 as shown.

[0069] S3. According to the daily material flux of the river, the extreme threshold index is calculated. The extreme threshold index includes the threshold of the extreme material flux and the daily change rate of the flux, as Figure 2 shown.

[0070] The percentile of the daily flux is the threshold for dividing the extreme high and low values of the material flux, and the daily change rate is used to judge the start and end processes of the extreme high flux.

[0071] The calculation formulas for the threshold of the extreme material flux and the daily change rate of the flux are as follows:

[0072] TL j = PERC(DL i , PT j )

[0073]

[0074] In the formula, TL is the threshold of the extreme material flux; DL is the daily material flux; PT is the percentile; LC is the daily change rate of the flux; i and j are the date and the extreme flux level respectively.

[0075] S4. According to the daily material flux and the extreme threshold index, the daily river material flux sequence under different extreme levels is obtained.

[0076] The extreme flux levels include extreme high flux and extreme low flux:

[0077] For the extreme high flux sequence, its sequence is the flux records exceeding the TL threshold. This sequence starts when LC is higher than the threshold of the daily change rate of the flux and ends when LC is lower than the decline threshold of the daily change rate of the flux;

[0078] Specifically, the extremely high-throughput sequence includes all process records of the start, process, and end of the throughput event. Its sequence is the throughput record exceeding the TL threshold. The sequence starts when the LC is higher than the throughput daily change rate threshold and ends when the LC is lower than the throughput daily change rate decline threshold. This time series includes a high-throughput start subsequence, a high-throughput middle subsequence, and a high-throughput end subsequence.

[0079] For the extremely low-throughput sequence, its sequence is the throughput record where DL is less than the specified TL threshold;

[0080] Specifically, the extremely low-throughput sequence is the throughput record where DL is less than the specified TL threshold, and this sequence does not include the changing sequences at the start and end.

[0081] The identified extremely high-throughput sequences and extremely low-throughput sequences are as Figure 4 shown.

[0082] S5. According to the daily river material throughput sequence, sum the values in the sequence to obtain the extreme values of river material throughput at different levels.

[0083] The calculation formulas for the extreme values of river material throughput at different types and levels are as follows:

[0084]

[0085] In the formula, RFC j is the extreme value of river material throughput at level j; DL is the daily material throughput; js and je are the start and end dates of the jth throughput extreme value respectively.

[0086] Figure 5 and Figure 6 are the identification results of the extremely high and extremely low throughput values respectively.

[0087] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only the specific implementation manners. Obviously, many modifications and changes can be made according to the content of this specification. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the present invention, so that those skilled in the relevant technical fields can understand and utilize the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A method for calculating extreme values ​​of river material flux, characterized in that: The following steps are involved: S1, obtain the flow data and material concentration data of a certain section of the river, where the time resolution of the flow data is not less than the daily scale; S2, constructing a river flux calculation model based on the flow data and material concentration data obtained in step S1, and calculating the daily material flux of the river; S3, calculating an extreme threshold index according to the daily material flux of the river, the extreme threshold index including a threshold of the extreme material flux and a daily change rate of the flux; S4, obtaining a daily material flux sequence of a river at different extreme levels according to the daily material flux and extreme threshold index; S5, according to the daily material flux sequence of the river, summing up the values ​​in the sequence, so as to obtain extreme values ​​of river material flux of different levels.

2. The method for calculating the extreme value of river material flux according to claim 1, characterized in that: In step S1, the flow data is continuous flow observation data on a daily or sub-daily scale, and the sequence length is not shorter than one hydrological year; the substance concentration data is the mass of a substance in a unit volume of water.

3. The method for calculating the extreme value of river material flux according to claim 1, characterized in that: The step S2 includes the following sub-steps: S21, construct river flux calculation model: The flow data and material concentration data were input into the LOADEST model, and the maximum likelihood method was selected to estimate the flux. The Akaike information criterion AIC and the Schwartz information criterion SPPC of different equations were calculated, and the equation with the lowest AIC and the largest SPPC was selected as the river flux calculation model. The fitting equation of the model is as follows: ln(L)=a0+a1LQ+a2Sin(2πD)+a3Cos(2πD)+a4D in, LQ=L(Q)-Center(Q) D=DT-Center(DT) Where, L is the daily flux of the substance (kg / d); LQ is the difference between the logarithm of the flow rate and the logarithm of the center value of the flow rate; D is the difference between the date and the center value of the date; Sin and Cos are sine and cosine functions respectively; Center(X) is the center value of X; is the average value of X; n is the sequence length of X; a0~a4 are the fitting coefficients of the equation; S22, determine the fitting coefficient.

4. The method for calculating the extreme value of river material flux according to claim 3, characterized in that: In step S3, the calculation formulas for the threshold of extreme material flux and the daily change rate of flux are as follows: TL j =MIN(DL i ,PT j ) Where TL is the threshold of extreme material flux; DL is the daily material flux; PT is the percentile; LC is the daily change rate of flux; i and j are the date and extreme flux level, respectively.

5. The method for calculating the extreme value of river material flux according to claim 4, characterized in that: In step S4, the extreme flux level includes extremely high flux and extremely low flux: For the extreme high flux sequence, the sequence is the flux record exceeding the TL threshold, which starts when the LC is higher than the flux daily change rate threshold and ends when the LC is lower than the flux daily change rate decrease threshold; For extremely low flux sequences, the sequences are flux records whose DL is less than the specified threshold of TL.

6. A method for calculating extreme values ​​of river material flux according to claim 5, characterized in that: In step S5, the calculation formulas for extreme values ​​of river material flux of different types and levels are as follows: In the formula, RFC j is the extreme value of river material flux of level j; DL is the daily material flux; js and je are the start and end dates of the jth flux extreme value, respectively.

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