A base flow segmentation method and device based on seasonal conductivity data correction

Abstract

The present invention discloses a baseflow segmentation method and device based on seasonal conductivity data correction, the method comprising: collecting data, including daily runoff and conductivity data; performing baseflow segmentation using the CMB method to obtain daily baseflow, and using the segmentation result as a standard for subsequent ECK method parameter correction; correcting the ECK method parameters year by year and season according to the CMB method segmentation result, using the daily baseflow data obtained by the CMB method as a standard, finding the ECK method parameter combination that minimizes the baseflow calculation error, and obtaining the optimal parameter combination in the flood season and the dry season; and performing baseflow segmentation calculation using the corrected ECK method optimal parameter combination. The present invention makes full use of the advantages of both the CMB method and the ECK method, not only can improve the accuracy and reliability of the baseflow segmentation results, but also can reduce the data sample requirements, and achieve the purpose of taking both high resolution and low data into consideration.

Description

Technical Field

[0001] The present invention relates to the technical field of river base flow segmentation, and in particular to a base flow segmentation method and device based on seasonal conductivity data correction. Background Art

[0002] River baseflow segmentation is the division of the ratio of surface runoff to baseflow in river runoff. The improvement and research of baseflow segmentation methods have gradually become a hot topic in recent years. Continuously improving the convenience and accuracy of baseflow segmentation methods, mastering the characteristic values ​​of rivers and basins and the relationship between various hydrological elements are of great significance to the calculation of runoff and hydrological simulation, as well as water resources evaluation and utilization, industrial and agricultural water supply planning, water security, and ecological environmental protection.

[0003] At present, the main baseflow segmentation methods can be roughly divided into two categories: one is the baseflow segmentation method based on the tracer method; the other is the segmentation method not based on the tracer method. Non-tracer methods mainly include graphical method, digital filtering method (ECK method), BRM method, PART method, etc. Its advantages are that the operation is relatively convenient and the accuracy is within an acceptable range; the disadvantages are that the reliability of the theoretical basis of the segmentation method and the accuracy of the segmentation results need to be further improved. Baseflow segmentation methods based on the tracer method include isotope tracer method, conductivity mass balance method (CMB method), etc. This type of method has high segmentation accuracy, reliable and accurate segmentation results, and clear physical meaning of parameters; but the operation is difficult and costly, and has high requirements for the development of detection work.

[0004] The present invention involves a digital filtering method and a conductivity mass balance method, and the principles of the two methods are introduced below. The digital filtering method originates from signal analysis, which divides the signal into a high-frequency signal and a low-frequency signal. It is believed that the direct runoff in hydrological analysis is similar to the high-frequency signal, and the baseflow is similar to the low-frequency signal. The high-frequency signal and the low-frequency signal in the water flow are separated by the digital filtering method, and then the runoff is divided into direct runoff and underground runoff (i.e., baseflow). The more widely used digital filtering methods include Lyne, Hollick, Chapman-Maxwell and Eckhardt filtering methods. Among them, the baseflow process line calculated by the Eckhardt digital filtering method (ECK method) can best reflect the specific confluence process. Assuming that there is a linear relationship between the outflow and storage capacity of the aquifer, the specific baseflow calculation can be performed by the following formula:

[0005]

[0006] In the formula, R BF·MAX is the maximum underground runoff index, α is the filtering parameter, q i and q i-1Respectively represent the underground runoff at the i-th and i-1-th moments (m 3 / s), Q i is the total runoff at time i (m 3 / s). If you want to calculate using the above formula, you need to determine the parameters α, R BF·MAX Eckhardt's research shows that α essentially expresses the decay process of base flow, has relatively little effect on the calculation results, and can generally be taken as 0.95-0.98; the maximum underground runoff index R BF·MAX Different empirical values ​​can be used under different hydrogeological conditions: 0.80 for perennial rivers in loose porous aquifers, 0.50 for seasonal rivers in loose porous aquifers, and 0.25 for seasonal rivers in weak permeable layers. The parameters in the formula can be determined by the above empirical values, and the base flow can be calculated using the ECK method.

[0007] The ECK method is derived from analogical speculation, and the physical meaning of the parameters is unclear. BF·MAX The value selection only takes into account the underlying surface and hydrological conditions, and simply selects values ​​from 0.25, 0.50, and 0.80, ignoring the dynamic changes of parameters within the year, which inevitably leads to large errors in the results and low calculation accuracy.

[0008] The conductivity mass balance method (CMB method) divides the process flow line generated by rainfall into different water sources based on the principle of tracer mass conservation and is based on actual physical processes. The CMB method assumes that the main water sources of the river (surface runoff and base flow) have characteristic conductivity values, and uses the high-frequency (generally daily scale) conductivity monitoring data of the river section or station to calculate the base flow q for each period according to the following formula: BF :

[0009]

[0010] In the formula, q BF Represents daily base flow (m 3 / s, Q represents daily runoff (m 3 / s), SC is the river conductivity value in the corresponding period (μs / cm), SC RO is the characteristic conductivity of the surface runoff end member, SC BF is the characteristic conductivity value of the base flow end member. Here Q and SC are measured values, and the parameter SC RO and SC BF The conductivity value is generally set to the conductivity value at the highest and lowest flow rates. Since the groundwater components in the river have passed through underground pores and other spaces during their formation, a large amount of soluble substances have been dissolved, and their conductivity value is significantly higher than that of surface water. Therefore, it is determined that the river flow is 100% replenished by the base flow when the river flow is the lowest and the conductivity value is the highest each year. The conductivity value at this time is the characteristic conductivity value of the base flow (SCBF ); Correspondingly, when the river runoff is the largest, the surface runoff is absolutely dominant in the river runoff, and the conductivity value is the lowest at this time, which is identified as the characteristic conductivity value of the surface runoff (SC RO ). The CMB method has high segmentation accuracy and clear physical meaning of parameters, but it is difficult to operate and has high cost.

[0011] The above tracer and non-tracer methods have their own advantages and disadvantages, so it is necessary to study a base flow segmentation method that can take into account the advantages of these two methods. Summary of the invention

[0012] In view of the above problems, the purpose of the present invention is to provide a baseflow segmentation method and device based on seasonal conductivity data correction. Based on the high accuracy of the CMB method, the results of the CMB method are used to correct the ECK method parameters on a year-by-year and seasonal basis, and the corrected parameters are used to calculate the subsequent baseflow, thereby improving the accuracy of the calculation.

[0013] To solve the above technical problems, the embodiments of the present invention provide the following solutions:

[0014] On the one hand, a baseflow segmentation method based on seasonal conductivity data correction is provided, comprising the following steps:

[0015] S1. Collect data, including daily runoff and conductivity data;

[0016] S2, using CMB method to segment base flow, obtain daily base flow, and use the segmentation result as the standard for subsequent ECK method parameter correction;

[0017] S3. According to the segmentation results of the CMB method, the ECK method parameters are corrected year by year and season by season. The daily base flow data obtained by the CMB method is used as the standard to find the ECK method parameter combination that minimizes the base flow calculation error, and the optimal parameter combination for the flood season and the dry season is obtained;

[0018] S4. Use the modified ECK method optimal parameter combination to perform base flow segmentation calculation.

[0019] Preferably, in step S1, the collected data include daily runoff Q and daily scale conductivity data SC, and the parameter SC is determined by the daily scale conductivity data SC. RO and SC BF , where SC RO is the annual minimum conductivity, SC BF is the maximum conductivity year by year.

[0020] Preferably, in step S2, the determined parameter SC RO and SC BF Substitute the daily runoff Q into formula (3) to obtain the daily base flow qBF-CMB :

[0021]

[0022] The calculated segmentation results serve as the standard for subsequent ECK method parameter correction.

[0023] Preferably, the step S3 specifically includes:

[0024] S31. Determine the number of days k in the flood season and dry season 1 , k 2 ;

[0025] k 1 = x, k 2 =366-k 1 , the specific number of days x in the flood season is determined according to the measured data sequence Q;

[0026] S32, proposed filter parameter α and maximum underground runoff index R in ECK method BF·MAX The value of

[0027] Among them, the value range of α is 0.9-1.0, R BF·MAX The value range of is 0-1.0; each takes values ​​one by one in the value range at intervals of 0.01 and 0.1, forming 9×9 parameter combinations with a total of 81 combinations;

[0028] S33. Determine the optimal parameters α and R in the flood season BF·MAX ;

[0029] Substitute a parameter combination of step S32 into formula (4) to calculate the flood season base flow q at time t t ; At this time, the calculated result may not be consistent with the actual situation, and the base flow may exceed the runoff, so the calculated q t Directly used to calculate q t+1 , need to compare q t With Q t The relationship between q t+1 ,q t The calculation method and value of

[0030]

[0031] In the formula, α(j), R BF·MAX (i) is any combination of parameters in the previous step S32; q t-1 is the base flow at time t-1, m 3 / s;Q t is the runoff at time t, which is the measured value, m 3 / s;

[0032] qt t In line with the actual situation, q t No change is equal to the calculated value. At this time, q is calculated according to formula (4): t+1 , change t-1 and t in the formula to t and t+1 respectively; q t ≥Q t This situation does not match the actual situation. It is necessary to analyze it in combination with specific data, compare the runoff size at t-1, t, and t+1, and determine q t ,q t+1 Get value;

[0033] The base flow rate at a certain time period t under different parameter combinations is calculated by formula (4), and the base flow rate obtained under different parameter combinations is compared with the q at the same time. BF-cMB Calculate the error; here we introduce the error matrix SD(i, j), and store the error results obtained by different parameter combinations in the error matrix; select the parameter combination with the smallest error from the error matrix for subsequent calculations, that is, to obtain the optimal parameters α, R for a certain period of time t BF·MAX ;

[0034] Repeat the above process, calculate the base flow and error of all periods t, t+1, t+2, ... in the flood season of a certain year under 81 parameter combinations, and select the parameter combination with the smallest error; then recycle and calculate the optimal parameter combination of the flood season in different years, that is, obtain the optimal parameters α, R BF·MAX ;

[0035] S34. Determine the optimal parameters α and R in the dry season BF·MAX ;

[0036] The same method as that used in step S33 to determine the optimal parameters for the flood season is used to obtain the optimal parameters α, R for the dry season in different years. BF·MAX .

[0037] Preferably, in step S4, the ECK method is used to perform subsequent base flow segmentation calculations according to the determined optimal parameter combination for the annual flood season and the dry season.

[0038] On the one hand, a base flow segmentation device based on seasonal conductivity data correction is provided, comprising:

[0039] Data collection module, used to collect data, including daily runoff and conductivity data;

[0040] The first calculation module is used to perform base flow segmentation using the CMB method to obtain the daily base flow, and use the segmentation result as a standard for subsequent ECK method parameter correction;

[0041] ​The parameter correction module is used to correct the ECK method parameters on an annual and seasonal basis according to the segmentation results of the CMB method, and to find the ECK method parameter combination that minimizes the base flow calculation error based on the daily base flow data obtained by the CMB method, so as to obtain the optimal parameter combination in the flood season and the dry season;

[0042] The second calculation module is used to perform base flow segmentation calculation using the modified ECK method optimal parameter combination.

[0043] Preferably, in the data collection module, the collected data include daily runoff Q and daily scale conductivity data SC, and the parameter SC is determined by the daily scale conductivity data SC. RO and SC BF , where SC RO is the annual minimum conductivity, SC BF is the maximum conductivity year by year.

[0044] Preferably, in the first calculation module, the determined parameter SC RO and SC BF Substitute the daily runoff Q into formula (3) to obtain the daily base flow q BF-CMB :

[0045]

[0046] The calculated segmentation results serve as the standard for subsequent ECK method parameter correction.

[0047] Preferably, the parameter correction module is specifically used for:

[0048] Determine the number of days k in the flood season and dry season 1 , k 2 ;

[0049] k 1 = x, k 2 =366-k 1 , the specific number of days x in the flood season is determined according to the measured data sequence Q;

[0050] The filter parameter α and the maximum underground runoff index R in the proposed ECK method BF·MAX The value of

[0051] Among them, the value range of α is 0.9-1.0, R BF·MAX The value range of is 0-1.0; each takes values ​​one by one in the value range at intervals of 0.01 and 0.1, forming 9×9 parameter combinations with a total of 81 combinations;

[0052] Determine the optimal parameters α and R in the flood season BF·MAX ;

[0053] Substitute a parameter combination of step S32 into formula (4) to calculate the flood season base flow q at time t t ; At this time, the calculated result may not be consistent with the actual situation, and the base flow may exceed the runoff, so the calculated q t Directly used to calculate q t+1 , need to compare q t With Q t The relationship between q t+1 ,q t The calculation method and value of

[0054]

[0055] In the formula, α(j), R BF·MAX (i) is any combination of parameters in the previous step S32; q t-1 is the base flow at time t-1, m 3 / s;Q t is the runoff at time t, which is the measured value, m 3 / s;

[0056] q t t In line with the actual situation, q t No change is equal to the calculated value. At this time, q is calculated according to formula (4): t+1 , change t-1 and t in the formula to t and t+1 respectively; q t ≥Q t This situation does not match the actual situation. It is necessary to analyze it in combination with specific data, compare the runoff size at t-1, t, and t+1, and determine q t ,q t+1 Get value;

[0057] The base flow rate at a certain time period t under different parameter combinations is calculated by formula (4), and the base flow rate obtained under different parameter combinations is compared with the q at the same time. BF-CMB Calculate the error; here we introduce the error matrix SD(i, j), and store the error results obtained by different parameter combinations in the error matrix; select the parameter combination with the smallest error from the error matrix for subsequent calculations, that is, to obtain the optimal parameters α, R for a certain period of time t BF·MAX ;

[0058] Repeat the above process, calculate the base flow and error of all periods t, t+1, t+2, ... in the flood season of a certain year under 81 parameter combinations, and select the parameter combination with the smallest error; then recycle and calculate the optimal parameter combination of the flood season in different years, that is, obtain the optimal parameters α, R BF·MAX ;

[0059] ​Determine the optimal parameters α and R in the dry season BF·MAX ;

[0060] The same method as that used in step S33 to determine the optimal parameters for the flood season is used to obtain the optimal parameters α, R for the dry season in different years. BF·MAX .

[0061] Preferably, in the second calculation module, the ECK method is used to perform subsequent base flow segmentation calculations according to the determined optimal parameter combination for the annual flood season and the dry season.

[0062] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0063] In an embodiment of the present invention, daily runoff and conductivity data are collected; base flow segmentation calculation is performed using the CMB method to obtain daily base flow, and the segmentation result is used as a standard for subsequent ECK method parameter correction; the ECK method parameters are corrected year by year and season by season according to the CMB method segmentation result, and the daily base flow data obtained by the CMB method is used as a standard to find the ECK method parameter combination that minimizes the base flow calculation error, and obtain the optimal parameter combination for the flood season and the dry season; finally, the base flow segmentation calculation is performed using the corrected ECK method optimal parameter combination. The present invention takes into account the advantages of both the CMB method and the ECK method, and uses the CMB method to correct the parameters of the ECK method year by year and season by season, and obtains the optimal parameter combination for different seasons to calculate the base flow, which can not only improve the accuracy and reliability of the base flow segmentation results, but also reduce the data sample requirements, thereby achieving the purpose of taking into account both high resolution and low data. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0065] Figure 1 is a flow chart of a baseflow segmentation method based on seasonal conductivity data correction provided by an embodiment of the present invention;

[0066] Figure 2 2 is a schematic diagram comparing the base flow segmentation results of the three methods provided in the embodiments of the present invention;

[0067] Figure 3 It is a structural block diagram of a base flow segmentation device based on seasonal conductivity data correction provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0068] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0069] The embodiment of the present invention provides a base flow segmentation method based on seasonal conductivity data correction, such as Figure 1 As shown, the base stream segmentation method comprises the following steps:

[0070] S1. Collect data, including daily runoff and conductivity data.

[0071] In this step, the collected data include daily runoff Q and daily scale conductivity data SC, and the parameter SC is determined by the daily scale conductivity data SC. RO and SC BF , where SC RO is the annual minimum conductivity, SC BF is the maximum conductivity year by year.

[0072] S2. Use the CMB method to segment the base flow to obtain the daily base flow, and use the segmentation result as the standard for subsequent ECK method parameter correction.

[0073] In this step, the determined parameter SC RO and SC BF Substitute the daily runoff Q into formula (3) to obtain the daily base flow q BF-CMB :

[0074]

[0075] The calculated segmentation results serve as the standard for subsequent ECK method parameter correction.

[0076] S3. According to the segmentation results of the CMB method, the ECK method parameters are corrected year by year and season by season. The daily base flow data obtained by the CMB method is used as the standard to find the ECK method parameter combination that minimizes the base flow calculation error, and obtain the optimal parameter combination in the flood season and the dry season.

[0077] Specifically, this step is implemented by writing a MATLAB program based on the ECK method principle and calculation formula (1) combined with the least squares method. The specific correction process is as follows:

[0078] S31. Determine the number of days k in the flood season and dry season 1 , k 2 ;

[0079] k 1 = x, k 2=366-k 1 The specific number of days x in the flood season is determined based on the measured data sequence Q.

[0080] S32, proposed filter parameter α and maximum underground runoff index R in ECK method BF·MAX The value of

[0081] Among them, the value range of α is 0.9-1.0, R BF·MAX The value range of is 0-1.0; each takes values ​​one by one within the value range at intervals of 0.01 and 0.1, forming 9×9 parameter combinations with a total of 81 combinations.

[0082] S33. Determine the optimal parameters α and R in the flood season BF·MAX ;

[0083] Substitute a parameter combination of step S32 into formula (4) to calculate the flood season base flow q at time t t ; At this time, the calculated result may not be consistent with the actual situation, and the base flow may exceed the runoff, so the calculated q t Directly used to calculate q t+1 , need to compare q t With Q t The relationship between q t+1 ,q t The calculation method and value of

[0084]

[0085] In the formula, α(j), R BF·MAX (i) is any combination of parameters in the previous step S32; q t-1 is the base flow at time t-1, m 3 / s;Q t is the runoff at time t, which is the measured value, m 3 / s;

[0086] q t t In line with the actual situation, q t No change is equal to the calculated value. At this time, q is calculated according to formula (4): t+1 , change t-1 and t in the formula to t and t+1 respectively; q t ≥Q t This situation does not match the actual situation. It is necessary to analyze it in combination with specific data, compare the runoff size at t-1, t, and t+1, and determine q t ,q t+1 Get value;

[0087] ​The base flow rate at a certain time period t under different parameter combinations is calculated by formula (4), and the base flow rate obtained under different parameter combinations is compared with the q at the same time. BF-CMB Calculate the error; here we introduce the error matrix SD(i, j), and store the error results obtained by different parameter combinations in the error matrix; select the parameter combination with the smallest error from the error matrix for subsequent calculations, that is, to obtain the optimal parameters α, R for a certain period of time t BF·MAX ;

[0088] Repeat the above process, calculate the base flow and error of all periods t, t+1, t+2, ... in the flood season of a certain year under 81 parameter combinations, and select the parameter combination with the smallest error; then recycle and calculate the optimal parameter combination of the flood season in different years, that is, obtain the optimal parameters α, R BF·MAX .

[0089] S34. Determine the optimal parameters α and R in the dry season BF·MAX ;

[0090] The same method as that used in step S33 to determine the optimal parameters for the flood season is used to obtain the optimal parameters α, R for the dry season in different years. BF·MAX .

[0091] Specifically, a parameter combination of step S32 is substituted into formula (4) to calculate the dry season base flow q at time t: t ; Similar to the calculation principle of flood season, it is necessary to compare q t With Q t The size relationship is used to determine q t+1 ,q t Calculation method and value of . Based on the obtained base flow, calculate its difference with the standard method result q BF-CMB Repeat the previous process, screen out the 81 errors, and pick out the parameter combination with the smallest error. This parameter combination is the optimal parameters α, R in the dry season of a certain year. BF·MAX By performing the same calculation for different years, we can obtain the optimal parameters for the dry season in different years.

[0092] S4. Use the modified ECK method optimal parameter combination to perform base flow segmentation calculation.

[0093] In this step, the ECK method is used to perform subsequent base flow segmentation calculations based on the determined optimal parameter combination for each year's flood season and dry season. The above calculation process can be completed using the MATLAB program.

[0094] In the embodiment of the present invention, considering that the CMB method is based on physical reality and is a relatively accurate method for base flow segmentation, the ECK method parameters are corrected by the CMB method results, and the subsequent base flows are calculated using the corrected parameters to improve the accuracy of the calculation.

[0095] Parameters α, R BF·MAX There will be certain fluctuations in different years, seasons and climates. In the flood season, most of the river recharge comes from precipitation, and the proportion of groundwater recharge will be relatively reduced. BF·MAX In the dry season, due to the decrease in precipitation, groundwater runoff becomes the main part of the recharge, and R BF·MAX The parameter is closely related to the season, and there are still errors in the parameters calculated over a long period of time or year by year. Based on this, the present invention selects the CMB calculation results of the seasonal monitoring data year by year to correct the ECK method parameters and calculate the parameters of different seasons (dry season, flood season) year by year. BF·MAX and α are taken in the range of 0-1.0, 0.9-1.0 with intervals of 0.1 and 0.01 respectively, and the baseflow segmentation results of different time periods are calculated one by one under various parameter value combinations. Taking the baseflow segmentation results of the CMB method as the benchmark, the parameter combination with the smallest difference from the CMB baseflow of the corresponding period is found as the optimal parameter combination for subsequent baseflow calculation. The advantages of the two methods are fully utilized, which can not only improve the accuracy and reliability of the baseflow segmentation results, but also reduce the demand for data samples, so as to achieve the goal of taking into account both high resolution and low data.

[0096] The following further illustrates the implementation mode of the present invention by using the method of the present invention to segment the base flow at a station in the Mississippi River Basin of the United States.

[0097] Step 1: Collect data. Collect daily flow Q and conductivity SC data for the same period.

[0098] The 06089000 station has 31 years (1969-1999) of daily-scale flow and conductivity data for the same period.

[0099] Step 2: Calculate base flow using the CMB method.

[0100] To calculate the base flow using the CMB method, it is necessary to determine the parameter SC RO and SC BF According to the meaning of the parameters, the minimum and maximum annual conductivity are selected as the parameter values. The determined parameters and the measured daily base flow Q are substituted into formula (3) to obtain the daily base flow q BF-CMB :

[0101]

[0102] The calculated results are used as the standard for subsequent ECK method parameter correction.

[0103] Step 3: Optimize ECK method parameters.

[0104] According to the annual dynamic characteristics of the 06089000 station, May to August is selected as the flood season, and the rest of the period is the dry season. The number of days in the flood season is k 1 123 days, dry season days k 2 is 243 days. BF-CMB Import the program and run it to get the parameters α, R of the dry season and flood season year by year. BF·MAX (See Table 1). The optimal parameters of the station in different periods were obtained by averaging the parameters of each season year by year, and the abnormal years (R BF·MAX For this site, the abnormal years are 1973, 1977, 1987, 1988, and 1992. The average of the parameters for the remaining years is 0.96 for the flood season. BF·MAX is 0.26; in the dry season, α is 0.93, R BF·MAX It is 0.64.

[0105] Table 1 Seasonal parameters after parameter optimization

[0106]

[0107] Step 4: Perform base flow segmentation by optimizing parameters.

[0108] Based on the optimal parameters determined previously, the base flow at different time periods is calculated step by step based on formula (1). This process is implemented through a program. After the program runs, the base flow q calculated using the optimized parameters is derived. BF-ECK优化 ( Figure 1 ).

[0109] In order to show the superiority of the optimized parameters, the segmentation results are compared with those of the common ECK empirical value method. The specific process of calculating the base flow segmentation results of the ECK empirical value method is as follows: First, the parameters α and R in the ECK calculation formula are determined by empirical values. BF·MAX , α ranges from 0.95 to 0.98, R BF·MAX Choose from 0.25, 0.50, and 0.80 according to the underlying surface and hydrological conditions. Secondly, determine the initial base flow q based on the measured data 1 : The initial time is the low water period, q 1 Numerically equal to Q 1 ; When the initial moment is the flood season, q 1 It is equal to the base flow calculated by CMB method at the same time. After determining the input quantity q 1 , parameters α, R BF·MAX Then, according to the formula, program in MATLAB to calculate the base flow q step by step. BF-经验值 .

[0110] The river at the selected site has water all year round and does not experience seasonal dry-up, so it is a perennial river. Therefore, the parameter R determined by the empirical value method is BF·MAX The value is 0.80. α has little effect on the results, so here we choose α as 0.98. Since the data starts in November, which is the dry season, the q 1 10.95m 3 / s. Substitute the determined parameters and initial values ​​into the program and import the runoff data Q, q BF-CMB . Run the program to export the base flow segmentation results obtained by the empirical value method.

[0111] Table 2 Annual base flow segmentation results of different methods

[0112]

[0113] Taking the CMB runoff process line as the benchmark, the segmentation results before and after parameter optimization are compared, such as Figure 1 As shown. It can be seen that the baseflow process line obtained by the ECK correction method for each year and season is closer to the CMB method in terms of general shape and numerical value. The error of the ECK method and the empirical value method for calculating parameter identification is compared with the CMB method. It is found that the ECK method after parameter optimization improves the accuracy of the result by about 66% compared with the empirical value method, which greatly improves the accuracy of baseflow segmentation. Similar conclusions can be obtained at other sites. In areas where conductivity data is difficult to obtain, the high-precision CMB method cannot be used directly. Through the optimization of ECK method parameter identification in this description, the calculation accuracy can be improved as much as possible under the existing data conditions.

[0114] Accordingly, an embodiment of the present invention further provides a base flow segmentation device based on seasonal conductivity data correction, such as Figure 3 As shown, the device comprises:

[0115] Data collection module, used to collect data, including daily runoff and conductivity data;

[0116] The first calculation module is used to perform base flow segmentation using the CMB method to obtain the daily base flow, and use the segmentation result as a standard for subsequent ECK method parameter correction;

[0117] The parameter correction module is used to correct the ECK method parameters on an annual and seasonal basis according to the segmentation results of the CMB method, and to find the ECK method parameter combination that minimizes the base flow calculation error based on the daily base flow data obtained by the CMB method, so as to obtain the optimal parameter combination in the flood season and the dry season;

[0118] The second calculation module is used to perform base flow segmentation calculation using the modified ECK method optimal parameter combination.

[0119] Furthermore, in the data collection module, the collected data include daily runoff Q and daily scale conductivity data SC, and the parameter SC is determined by the daily scale conductivity data SC. RO and SC BF , where SC RO is the annual minimum conductivity, SC BF is the maximum conductivity year by year.

[0120] Furthermore, in the first calculation module, the determined parameter SC RO and SC BF Substitute the daily runoff Q into formula (3) to obtain the daily base flow q BF-CMB :

[0121]

[0122] The calculated segmentation results serve as the standard for subsequent ECK method parameter correction.

[0123] Furthermore, the parameter correction module is specifically used for:

[0124] Determine the number of days k in the flood season and dry season 1 , k 2 ;

[0125] k 1 = x, k 2 =366-k 1 , the specific number of days x in the flood season is determined according to the measured data sequence Q;

[0126] The filter parameter α and the maximum underground runoff index R in the proposed ECK method BF·MAX The value of

[0127] Among them, the value range of α is 0.9-1.0, R BF·MAX The value range of is 0-1.0; each takes values ​​one by one in the value range at intervals of 0.01 and 0.1, forming 9×9 parameter combinations with a total of 81 combinations;

[0128] Determine the optimal parameters α and R in the flood season BF·MAX ;

[0129] Substitute a parameter combination of step S32 into formula (4) to calculate the flood season base flow q at time t t ; At this time, the calculated result may not be consistent with the actual situation, and the base flow may exceed the runoff, so the calculated q t Directly used to calculate q t+1 , need to compare q t With Q t The relationship between q t+1 ,q tThe calculation method and value of

[0130]

[0131] In the formula, α(j), R BF·MAX (i) is any combination of parameters in the previous step S32; q t-1 is the base flow at time t-1, m 3 / s;Q t is the runoff at time t, which is the measured value, m 3 / s;

[0132] q t t In line with the actual situation, q t No change is equal to the calculated value. At this time, q is calculated according to formula (4): t+1 , change t-1 and t in the formula to t and t+1 respectively; q t ≥Q t This situation does not match the actual situation. It is necessary to analyze it in combination with specific data, compare the runoff size at t-1, t, and t+1, and determine q t ,q t+1 Get value;

[0133] The base flow rate at a certain time period t under different parameter combinations is calculated by formula (4), and the base flow rate obtained under different parameter combinations is compared with the q at the same time. BF-CMB Calculate the error; here we introduce the error matrix SD(i, j), and store the error results obtained by different parameter combinations in the error matrix; select the parameter combination with the smallest error from the error matrix for subsequent calculations, that is, to obtain the optimal parameters α, R for a certain period of time t BF·MAX ;

[0134] Repeat the above process, calculate the base flow and error of all periods t, t+1, t+2, ... in the flood season of a certain year under 81 parameter combinations, and select the parameter combination with the smallest error; then recycle and calculate the optimal parameter combination of the flood season in different years, that is, obtain the optimal parameters α, R BF·MAX ;

[0135] Determine the optimal parameters α and R in the dry season BF·MAX ;

[0136] The same method as that used in step S33 to determine the optimal parameters for the flood season is used to obtain the optimal parameters α, R for the dry season in different years. BF·MAX .

[0137] Furthermore, in the second calculation module, the ECK method is used to perform subsequent base flow segmentation calculations according to the determined optimal parameter combination for the annual flood season and the dry season. ​

[0138] The device of this embodiment can be used to perform Figure 1 The technical solution of the method embodiment shown has similar implementation principles and technical effects, which will not be repeated here.

[0139] In summary, the baseflow segmentation method and device provided by the embodiment of the present invention collects daily runoff and conductivity data; uses the CMB method to segment the baseflow to obtain the daily baseflow, and uses the segmentation result as the standard for subsequent ECK method parameter correction; according to the CMB method segmentation result, the ECK method parameters are corrected year by year and season by season, and the daily baseflow data obtained by the CMB method is used as the standard to find the ECK method parameter combination that minimizes the baseflow calculation error, and obtain the optimal parameter combination in the flood season and the dry season; finally, the corrected ECK method optimal parameter combination is used to perform baseflow segmentation calculation. The present invention takes into account the advantages of both the CMB method and the ECK method, and uses the CMB method to correct the parameters of the ECK method year by year and season by season to obtain the optimal parameter combination for baseflow calculation, which can not only improve the accuracy and reliability of the baseflow segmentation results, but also reduce the data sample requirements, so as to achieve the purpose of taking into account both high resolution and low data.

[0140] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A baseflow segmentation method based on seasonal conductivity data correction, characterized in that: The following steps are involved: S1. Collect data, including daily runoff and conductivity data; S2, using CMB method to segment base flow, obtain daily base flow, and use the segmentation result as the standard for subsequent ECK method parameter correction; S3. According to the segmentation results of the CMB method, the ECK method parameters are corrected year by year and season by season. The daily base flow data obtained by the CMB method is used as the standard to find the ECK method parameter combination that minimizes the base flow calculation error, and the optimal parameter combination for the flood season and the dry season is obtained; The step S3 specifically includes: S31, determine the number of days k1 and k2 of the flood season and the dry season; k1=x、k2=366-k1, the specific number of days x in the flood season is determined according to the measured data sequence Q; S32, proposed filter parameter α and maximum underground runoff index R in ECK method BF·MAX The value of Among them, the value range of α is 0.9-1.0, R BF·MAX The value range of is 0-1.0; each takes values ​​one by one in the value range at intervals of 0.01 and 0.1, forming 9×9 parameter combinations with a total of 81 combinations; S33. Determine the optimal parameters α and R in the flood season BF·MAX ; Substitute a parameter combination of step S32 into formula (4) to calculate the flood season base flow q at time t t ; At this time, the calculated result may not be consistent with the actual situation, and the base flow may exceed the runoff, so the calculated q t Directly used to calculate q t+1 , need to compare q t With Q t The relationship between q t+1 ,q t The calculation method and value of In the formula, α(j), R BF·MAX (i) is any combination of parameters in the previous step S32; q t-1 is the base flow at time t-1, m 3 / s;Q t is the runoff at time t, which is the measured value, m 3 / s; q t t In line with the actual situation, q t No change is equal to the calculated value. In this case, q is calculated according to formula (4): t+1 , change t-1 and t in the formula to t and t+1 respectively; q t ≥Q t This situation does not match the actual situation. It is necessary to analyze it in combination with specific data, compare the runoff size at t-1, t, and t+1, and determine q t ,q t+1 Get value;​ The base flow rate at a certain time period t under different parameter combinations is calculated by formula (4), and the base flow rate obtained under different parameter combinations is compared with the q at the same time. BF-CMB Calculate the error; here we introduce the error matrix SD(i, j), and store the error results obtained by different parameter combinations in the error matrix; select the parameter combination with the smallest error from the error matrix for subsequent calculations, that is, to obtain the optimal parameters α, R for a certain period of time t BF·MAX ; Repeat the above process, calculate the base flow and error of all periods t, t+1, t+2, ... in the flood season of a certain year under 81 parameter combinations, and select the parameter combination with the smallest error; then recycle and calculate the optimal parameter combination of the flood season in different years, that is, obtain the optimal parameters α, R BF·MAX ; S34. Determine the optimal parameters α and R in the dry season BF·MAX ; The same method as that used in step S33 to determine the optimal parameters for the flood season is used to obtain the optimal parameters α, R for the dry season in different years. BF·MAX ; S4. Use the modified ECK method optimal parameter combination to perform base flow segmentation calculation.

2. The base flow segmentation method according to claim 1, characterized in that: In step S1, the collected data include daily runoff Q and daily scale conductivity data SC, and the parameter SC is determined by the daily scale conductivity data SC. RO and SC BF , where SC RO is the annual minimum conductivity, SC BF is the maximum conductivity year by year.

3. The base flow segmentation method according to claim 2, characterized in that: In step S2, the determined parameter SC RO and SC BF , daily runoff Q is substituted into formula (3) to obtain the daily base flow q BF-CMB : The calculated segmentation results serve as the standard for subsequent ECK method parameter correction.

4. The base flow segmentation method according to claim 1, characterized in that: In step S4, the ECK method is used to perform subsequent base flow segmentation calculations according to the determined optimal parameter combination for the annual flood season and the dry season.

5. A base flow segmentation device based on seasonal conductivity data correction, characterized in that: include: Data collection module, used to collect data, including daily runoff and conductivity data; The first calculation module is used to perform base flow segmentation using the CMB method to obtain the daily base flow, and use the segmentation result as a standard for subsequent ECK method parameter correction; The parameter correction module is used to correct the ECK method parameters on an annual and seasonal basis according to the segmentation results of the CMB method, and to find the ECK method parameter combination that minimizes the base flow calculation error based on the daily base flow data obtained by the CMB method, so as to obtain the optimal parameter combination in the flood season and the dry season; The parameter correction module is specifically used for: Determine the number of days k1 and k2 of the flood season and dry season; k1=x、k2=366-k1, the specific number of days x in the flood season is determined according to the measured data sequence Q; The filter parameter α and the maximum underground runoff index R in the proposed ECK method BF·MAX The value of Among them, the value range of α is 0.9-1.0, R BF·MAX The value range of is 0-1.0; each takes values ​​one by one in the value range at intervals of 0.01 and 0.1, forming 9×9 parameter combinations with a total of 81 combinations; Determine the optimal parameters α and R in the flood season BF·MAX ; Substitute a parameter combination of step S32 into formula (4) to calculate the flood season base flow q at time t t ; At this time, the calculated result may not be consistent with the actual situation, and the base flow may exceed the runoff, so the calculated q t Directly used to calculate q t+1 , need to compare q t With Q t The relationship between q t+1 ,q t The calculation method and value of In the formula, α(j), R BF·MAX (i) is any combination of parameters in the previous step S32; q t-1 is the base flow at time t-1, m 3 / s;Q t is the runoff at time t, which is the measured value, m 3 / s; q t t In line with the actual situation, q t No change is equal to the calculated value. In this case, q is calculated according to formula (4): t+1 , change t-1 and t in the formula to t and t+1 respectively; q t ≥Q t This situation does not match the actual situation. It is necessary to analyze it in combination with specific data, compare the runoff size at t-1, t, and t+1, and determine q t ,q t+1 Get value;​ The base flow rate at a certain time period t under different parameter combinations is calculated by formula (4), and the base flow rate obtained under different parameter combinations is compared with the q at the same time. BF-CMB Calculate the error; here we introduce the error matrix SD(i, j), and store the error results obtained by different parameter combinations in the error matrix; select the parameter combination with the smallest error from the error matrix for subsequent calculations, that is, to obtain the optimal parameters α, R for a certain period of time t BF·MAX ; Repeat the above process, calculate the base flow and error of all periods t, t+1, t+2, ... in the flood season of a certain year under 81 parameter combinations, and select the parameter combination with the smallest error; then recycle and calculate the optimal parameter combination of the flood season in different years, that is, obtain the optimal parameters α, R BF·MAX ; Determine the optimal parameters α and R in the dry season BF·MAX ; The same method as that used in step S33 to determine the optimal parameters for the flood season is used to obtain the optimal parameters α, R for the dry season in different years. BF·MAX ; The second calculation module is used to perform base flow segmentation calculation using the modified ECK method optimal parameter combination.

6. The base flow segmentation device according to claim 5, characterized in that: In the data collection module, the collected data include daily runoff Q and daily scale conductivity data SC, and the parameter SC is determined by the daily scale conductivity data SC. RO and SC BF , where SC RO is the annual minimum conductivity, SC BF is the maximum conductivity year by year.

7. The base flow segmentation device according to claim 6, characterized in that: In the first calculation module, the parameter SC is determined RO and SC BF , daily runoff Q is substituted into formula (3) to obtain the daily base flow q BF-CMB : The calculated segmentation results serve as the standard for subsequent ECK method parameter correction.

8. The base flow segmentation device according to claim 5, characterized in that: In the second calculation module, the ECK method is used to perform subsequent base flow segmentation calculations according to the determined optimal parameter combination for the annual flood season and the dry season.

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