CN117033888A - Watershed confluence unit line pushing method based on segmentation base flow - Google Patents
Watershed confluence unit line pushing method based on segmentation base flow Download PDFInfo
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Abstract
The application provides a river basin converging unit line pushing method based on a dividing base flow, which relates to the technical field of hydraulic engineering and comprises the following steps: selecting a rainfall station with rainfall records in an origin-destination time period by a Thiessen polygon method, and obtaining rainfall data sequences at equal time intervals according to precipitation data by an accumulation interpolation method; judging weight according to the water collection interval information, and obtaining a surface average precipitation sequence after weighted average; calculating a net rain process based on the surface average precipitation sequence; judging a starting point and an ending point of the base stream segmentation according to the rain purifying process, and obtaining a base stream process by linear interpolation; subtracting the rain-purifying process from the subinterval production process of the water collecting interval, dividing the base flow, and setting a triangular unit line; and carrying out local optimization on the triangular unit line to obtain an optimized unit line. The application carries out the estimation of the unit line based on the steps, improves the efficiency of estimating the unit line, is simpler and more practical compared with the prior art, and further improves the precision of the unit line.
Description
Technical Field
The application relates to the technical field of hydraulic engineering, in particular to a method based on dividing a basic flow unit line.
Background
The traditional method for evaluating the drainage basin confluence unit line comprises the following steps: according to the analysis method of directly deducing the unit line by definition, the trial-and-error method of correcting according to the outlet process line of the drainage basin after assuming the initial unit line, the least square method of the equation set to be solved, and the like. The analysis method is always in a sawtooth shape or even in a negative value, and a smoothing treatment method is always needed to be used; the difficulty of the trial-and-error method is that the initial assumption is difficult, and unreasonable phenomenon is likely to occur in the trial-and-error process; the least square method is perfect in principle, but saw-tooth oscillation occurs.
Along with the development of computer technology, various man-machine interaction modes gradually appear to calculate and select a unit line, researchers are provided with a time period change range of an initial unit line according to experience, a trial and error method is adopted, and the unit line meeting the precision requirement is selected by adjusting the change increment of each time period of the unit line; shang Chengyou, zhang Xiangdong and the like adopt a least square method to calculate an initial unit line, and adopt a manual interaction mode to correct the initial unit line to obtain a smooth unit line without saw teeth, and the method has higher requirement for solving an equation set and is not easy to master; dong Gugen and the like adopt an API model, and the artificial setting of flood diversion, base flow and stable infiltration rate, artificial setting of the allowed iteration error and the maximum iteration number of the Seidel iteration method, artificial screening of flood diversion for calculating a comprehensive unit line and the like are completed by a graphic interaction technology, so that the unit line man-machine interaction is deduced.
Disclosure of Invention
The application provides a drainage basin converging unit line pushing method based on a dividing base flow, and aims to solve the problems that various methods in the traditional technology are difficult to use and the efficiency of pushing unit lines is low.
In order to achieve the above object, the present application provides the following technical solutions: a river basin conflux unit line deducing method based on a dividing base flow comprises the following steps:
selecting a water collecting area or a subinterval, and selecting a site with precipitation data in the water collecting area or the subinterval origin-destination time period by a Thiessen polygon method;
obtaining a precipitation data sequence with equal time intervals through an accumulation interpolation method based on precipitation data of the station;
judging site weights according to the precipitation data sequences of the water collecting interval or the subinterval, and obtaining a surface average precipitation sequence after weighting and averaging the weights of all sites in the water collecting interval and the subinterval;
acquiring a rain purifying process based on the surface average precipitation sequence;
judging a starting point and an ending point of the base flow segmentation according to a rain purifying process and a flow generating process, and obtaining the base flow process by using a linear interpolation method based on the starting point and the ending point of the base flow segmentation;
setting a triangle unit line as an initial value unit line on the basis of basic flow segmentation;
and carrying out local optimization on the initial value unit line by adopting an ant colony algorithm, and deducing the unit line after local optimization.
Preferably, after the water collecting area or subinterval is acquired, field flood data is selected, after the outlet site of the flood is determined, no control site is selected or not selected at the upstream, and the research range is the water collecting area from the outlet site to the water diversion ridge;
after determining the exit site, one or more control sites are upstream and selected, and the scope of investigation is a subinterval above the exit site and below the upstream control site.
Preferably, the obtaining of the flow production process specifically includes the steps of:
calculating the confluence process of flood branches to the sections of the outlet sites by using a Ma Sijing heel method;
and subtracting the data after the flood tributaries are converged by using the measured data of the outlet station to obtain the stream production data, and obtaining the stream production process according to the stream production data.
Preferably, when calculating the rain purifying process based on the surface average precipitation sequence, dividing the water loss according to the method of 1mm of initial loss and 1mm of later loss to obtain the rain purifying process of each field flood.
Preferably, a triangle unit line is set as an initial value unit line on the basis of base stream segmentation, and the initial value unit line comprises the following parameters:
peak value, which is the measured flood peak divided by the net rainfall;
the rising time period number is rising time-rainfall start time;
the number of the flood period is peak time-rainfall start time;
the total duration of the unit line is the total time of flood diversion and the rainfall start time.
Preferably, the triangle unit line includes four control parameters, specifically:
triangle endpoint: iEnd, the minimum value is 1, and the maximum value is the total time period length of the selected flood;
triangle vertex abscissa: iMid, minimum value is 1, maximum value is 2/3 of iEnd;
triangle starting point: iBeg, minimum value is 0, maximum value is iMid;
triangle peak: uMax, minimum value is 0, maximum value is Qmax/Pmax of the secondary flood.
Preferably, the step of obtaining the triangle unit line includes the steps of:
the triangular unit line is obtained by using the SCE-UA algorithm, taking the four control parameters as selection objects, taking Nash efficiency coefficient as a selection index, taking total error <100% and peak time error <10 as boundary conditions, and taking improvement rate of two selection results before and after <0.01 as exit conditions.
Preferably, the initial value of the unit line is set by using an ARS algorithm with the initial value unit line initial value and the initial value of the unit line three elements is preferably set with the NSCE closest to 1 as a target.
Preferably, the local optimization of the initial value unit line by adopting an ant colony algorithm includes the steps of:
and (3) constructing judgment indexes:
wherein: q (Q) oi Is the measured flow; q (Q) ci The flow is simulated by using an initial value unit line;
for each value u of the unit line u i Respectively calculating corresponding judgment indexes e after correction of +/-1% i+ And e i- ；
The original judgment index is replaced by the correction with the maximum improvement of the judgment index, a new initial value is obtained, and iteration is sequentially carried out until the correction of the judgment index is smaller than the error line;
the logarithmic value is negative value u i First, the correction is carried out to the value u i Half of the former value, i.e. 0.5u i-1 ；
For adjacent values u after negative values i+1 First, correcting the value to be adjacent value u i+1 Half of (1), i.e. 0.5u i+1 ；
The ant colony algorithm is utilized, n or n+1 unit lines are taken as selection objects, half of deterministic coefficient and peak value error is taken as selection indexes, total error <50%, peak time error < = 1 are taken as boundary conditions, improvement rate of two selection results before and after is taken as exit conditions, and the unit lines after local optimization are obtained.
Preferably, the unit line after the local optimization is convolved with the rain purifying process to obtain the simulation data of the runoff process.
Compared with the prior art, the application has the following beneficial effects: the application provides a river basin converging unit line pushing method based on a dividing base flow, which is characterized in that a base flow dividing starting point and an end point are manually judged according to a rain purifying process and a flow generating process, the base flow dividing process is obtained by linear interpolation, the base flow dividing is realized, a triangular unit line is set as an initial value of the unit line, the triangular unit line is locally optimized by using an ant colony algorithm, fine adjustment is carried out on the line type, pushing and optimization of the unit line are carried out, the efficiency of pushing the unit line is improved, the obtained unit line is more stable and reliable, and compared with the prior art, the method is simpler and more practical, and meanwhile, the accuracy of the unit line is further improved.
Drawings
FIG. 1 is a verification result of river confluence provided by the application;
FIG. 2 is a process of base stream segmentation provided by the present application;
FIG. 3 is a graph showing the fitting result of triangle unit lines provided by the present application;
FIG. 4 is a graph showing the result of optimizing a unit line according to the present application;
FIG. 5 is a representative unimodal historical process line provided by the present application;
fig. 6 is a schematic diagram of a ten-room drainage basin rainfall station distribution provided by the application.
Detailed Description
The following describes the embodiments of the present application further with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical aspects of the present application, and are not intended to limit the scope of the present application.
After the historical flood is selected, a unit line is needed to be deduced, the unit line is deduced by utilizing the historical flood, then a water source is needed to be divided into underground runoff and surface runoff, the underground runoff is generally regarded as a base flow, therefore, the flow process line is needed to be divided into the base flow, and the measured flow is subtracted from the base flow to obtain the surface runoff. The intelligent auxiliary system is mainly used for dividing the base flow and carrying out unit line estimation, so that the efficiency of unit line estimation and the flood-taking simulation capability can be improved.
Referring to fig. 1-4, the application provides a drainage basin confluence unit line estimation method based on a segmentation base flow, which comprises the following steps:
step S1: and selecting a water collecting area or a subinterval, and selecting a site with precipitation data in the water collecting area or the subinterval origin-destination time period by using a Thiessen polygon method.
Step S11: after preparing the session flood data and determining the exit site, if there is no or no control site upstream, the scope of investigation is the water collection interval above the exit site up to the watershed.
Step S12: if one or more control sites are upstream and selected, the scope of investigation is a subinterval above the egress site and below the upstream control site (also known as tributary site).
Wherein, the preparation field flood data is: in the actual measurement hydrologic data of the river basin, a plurality of times of rain and flood processes which are representative in terms of flood magnitude and rainfall space-time distribution are selected. The duration of each rainfall is short, the peak shape of the flood process is complete, and the flood process is preferably a single peak or a compound peak flood process which is easy to be divided into single peaks.
According to the surface average precipitation in the water collecting area or the subinterval, the flow process line diagram of the outlet and the tributary (if any) is adopted, the starting time of the precipitation in the field and the ending time after the water withdrawal are manually judged, and the starting and the ending time are as follows: the start time is based on the closest time to the selected time 2, 8, 14, 20 before the selected time; the end time is based on the time closest to the selected time 2, 8, 14, 20; the actual flood time period may be 6 hours more than the selected period.
Step S2: and obtaining a precipitation data sequence at equal time intervals through an accumulation interpolation method based on precipitation data of the station.
For the traffic sequence: the data sequence of the equal time interval is obtained according to linear interpolation. For precipitation data: and selecting a rainfall station with precipitation records in an origin-destination time period according to a Thiessen polygon method, and obtaining the data sequence of the equal time interval according to the measured data by an accumulation interpolation method.
Step S3: and judging the site weight according to the rainfall data sequence information of the water collecting area or the subinterval, and obtaining the surface average rainfall sequence after weighting and averaging the weights of all sites in the water collecting area or the subinterval.
Step S4: and acquiring a net rain process based on the surface average precipitation sequence.
Step S41: based on the obtained surface average precipitation sequence, dividing the water loss according to the method of 1mm of initial loss and 1mm of later loss, and obtaining the calculated net rain process of each field flood.
Step S5: judging the starting point and the end point of the base stream segmentation according to the rain purifying process and the flow generating process, and obtaining the base stream process by using linear interpolation.
The acquisition of the flow production process specifically comprises the following steps:
step S51: the confluence of the tributaries to the outlet section was calculated using Ma Sijing root method.
Step S52: and subtracting the data after the flood tributaries are converged by using the measured data of the outlet station to obtain the stream production data, and obtaining the stream production process according to the stream production data.
In the process of rain purification, the starting point and the end point of the base flow segmentation are manually judged. The "net flow process" (flow process matched to the net rain process) follows the base flow process of the produced flow Cheng Jianqu. Fig. 2 is a process of base stream segmentation.
And when Ma Sijing methods are used for calculating the converging process from the tributaries to the outlet section, the related parameters are determined by adopting a man-machine interaction and cyclic trial calculation mode. An improved ARS (Adaptive Random Search method, variable domain decreasing random search algorithm) supported equine parameter automatic selection function may also be used. Note that the automatic selection of equine parameters is only most reasonable when the spatial distribution of precipitation is uniform, and manual judgment and adjustment are needed under other conditions. FIG. 1 shows the result of channel confluence verification.
Step S6: a triangle unit line is set as an initial value unit line on the basis of basic flow segmentation.
Wherein the initial value unit line includes the following parameters: the peak value is approximately equal to the actual measured flood peak divided by the net rainfall, the rising time period is approximately equal to the rising time-rainfall start time, the rising time period is approximately equal to the peak time-rainfall start time, and the total unit line duration is approximately equal to the total flood time-rainfall start time. With this as an initial value, an ARS algorithm is used to select and set the initial value of the three elements of the unit line with NSCE closest to 1 as a target.
The four control parameters of the triangle unit line are respectively:
triangle endpoint: and iEnd, the minimum value is 1, and the maximum value is the total period length of the selected flood.
Triangle vertex abscissa, iMid, minimum is 1, maximum takes 2/3 of iEnd.
Triangle starting point: iBeg, minimum is 0 and maximum is iMid.
Triangle peak: uMax, minimum is 0 and maximum is Qmax/Pmax for the next flood.
The step of obtaining the triangle unit line comprises the following steps: the four parameters are used as selection objects, the Nash efficiency coefficient is used as a selection index, the total error is 100%, the peak time error is 10 as a boundary condition, and the improvement of the two selection results is 0.01 as an exit condition to obtain a triangle unit line. Fig. 3 is the result of a triangle unit line fit. In order to increase stability (i.e., not overflow at different locations and under data conditions, a result is obtained), the boundary condition settings are relaxed at the cost of slightly longer computation time.
Step S7: and carrying out local optimization on the initial value unit line by adopting an ant colony algorithm, and deducing the unit line after local optimization.
The fitting optimization is carried out on the initial value unit line, and the steps are as follows:
step S71: structure judgment index
Wherein: q (Q) oi Is the measured flow; q (Q) ci Is the flow rate modeled using the initial unit line.
Step S72: for each value u of the unit line u i Respectively calculating corresponding judgment indexes e after correction of +/-1 percent i+ And e i- 。
Step S73: the original judgment index is replaced by the correction with the maximum improvement of the judgment index, a new initial value (sequence) is obtained, and the iteration is sequentially carried out until the correction (improvement) of the judgment index is smaller than an error line (such as 0.01).
Acceleration of intelligent correction:
the method also comprises the step of processing the tail sawtooth phenomenon of the unit line u, and comprises the following steps:
step S74: for the possible aliasing of the u tail of the unit line, for a negative value of u i First corrected to half of its previous value, i.e. 0.5u i-1 。
Step S75: for adjacent u after negative value i+1 First corrected to half its value, i.e. 0.5u i+1 。
Step S76: the ant colony algorithm is utilized, n or n+1 unit lines are taken as selection objects, half of deterministic coefficient and peak value error is taken as selection indexes, total error <50%, peak time error < = 1 are taken as boundary conditions, improvement of two selection results before and after is taken as exit conditions, and a unit line after local optimization is obtained. Fig. 4 shows the results obtained by unit line optimization.
In the local optimization process, the 'saw tooth' phenomenon of the final unit line result is avoided through the strict constraint of each numerical value variation range.
Experience has shown that: when flood is selected, the larger the rainfall in the first period is, the more stable and reliable the obtained unit line is.
And convolving the unit line after local optimization with the rain purifying process to obtain simulation data of the runoff process.
Example 1
In recent years, natural disasters frequently occur, flood disasters are particularly remarkable, and useful information is obtained from limited historical flood data so that reasonable flood forecast can be performed, and economic loss and casualties can be effectively reduced. The unit line can comprehensively reflect the yield and convergence conditions in the area, can be used for flood forecast and has a good effect. Based on different causes of flood, as shown in fig. 6, the application selects ten river basins of east Liaohe as research objects, selects 40 historical flood in 1980-1995 for research on the basis of re-analyzing historical data, and proposes an intelligent auxiliary mode for base stream segmentation in research and respectively deduces corresponding unit lines according to the selected historical flood: the river confluence inspection is completed through Ma Sijing methods supported by an ARS algorithm, basic flow segmentation is performed through man-machine interaction, an intelligent auxiliary system for estimating unit lines is constructed, the ARS algorithm is adopted, the Nash efficiency coefficient closest to 1 is selected as a target, initial values of three elements of the unit lines are set, and the unit lines are estimated and selected in a mode of fine adjustment of the line types according to the actual measurement runoff process by an ant colony algorithm. The result shows that the method improves the efficiency of unit line estimation on the premise of ensuring the unit line estimation effect.
Liaohe river basin is one of seven big river basins in China, liaohe is an optical head mountain originated from seven old mountains in Pingquan city of Hebei province, the whole length is 1345km, the whole river spans four provinces of Hebei, liaoning, jilin and inner Mongolia, and Dong Liaohe is a big tributary on the upstream east side of Liaohe. As shown in fig. 6, the subject selected in the present application is a ten-house area of the eastern Liao river basin. The east Liao river basin is distributed in the south-middle of Jilin province, the geographic position is 123 DEG 39-125 DEG 32 'in the east longitude, 42 DEG 37-44 DEG 09' in the North latitude, the east face is a large sand river, the west face is connected with the west Liao river, the south face is a Jiangsu table river, and the North face is an Ide river. The full length of the east Liaoriver is 360km, and the area of the river basin is 11306km 2 170km in the east-west direction, 58km in the north-south direction, 562.6mm of average precipitation in the river basin for many years, uneven precipitation distribution, high in the north-east, low in the south-west direction of the river basin, mainly black soil in soil distribution and mainly broad-leaved mixed forests and grasslands in vegetation.
The east Liao river basin is affected by geographical position distribution, sea-land distribution and topography, the space-time distribution of rainfall in the river basin is uneven, the rainfall is concentrated for 6-9 months and accounts for 60% -70% of annual rainfall, the annual average rainfall on the upstream is 700mm, the annual average rainfall on the downstream is 450mm, the trend of decreasing from upstream to downstream is shown, the annual average evaporation capacity is 800-1020 mm, and the trend of increasing from upstream to downstream is shown.
The actual measurement flood field time selection is based on actual measurement flow data of ten stations in the east Liao river basin, the rain and flood data of the ten stations in 1980-1995 are selected for historical flood selection, the flow data of the ten stations and the average surface rain data obtained through calculation are imported into a database, the total flood amount and the early-stage influence rain can be calculated through drawing, and the unimodal flood can be found intuitively. Wherein the representative years of flood are 1984, 1985, 1986 and 1994, the representative years of flood are 1986, 1990, 1991 and 1995, and the representative years of flood are 1980, 1981, 1987, 1988 and 1992. In total, 40 floods were selected, and the peak time, the flood peak flow rate and the total rainfall data are shown in table 1. The results of a random selection of a flood are shown as a rainflood course line with peak time of 7 months and 19 days 5 in 1988, as shown in fig. 5. In actual use, the user can select a plurality of times of representative rain Hong Guocheng in terms of flood magnitude and rainfall space-time distribution, and manually judge the start time of the precipitation and the end time after water withdrawal according to the surface average precipitation in the water collection region and the outlet flow process line diagram.
Table 1 flood selection results table
In the application, a representative rain and flood process is selected according to the selected historical flood data. According to the surface average precipitation in the water collection interval and the outlet flow process line diagram, manually judging the starting time of the field precipitation and the ending time after water withdrawal, aiming at the origin-destination time: the start time is based on the closest time to the selected time 2, 8, 14, 20 before the selected time; the end time is based on the time closest to the selected time 2, 8, 14, 20; the actual flood time period may be 6 hours more than the selected period. For the traffic sequence: the data sequence of the equal time interval is obtained according to linear interpolation. For precipitation data: selecting a rainfall station with precipitation records in an origin-destination time period according to a Thiessen polygon method, and obtaining a data sequence of an equal time interval from measured data according to an accumulation interpolation method; and judging the weight according to the water collection interval information, and obtaining the surface average precipitation sequence after weighted average. The rain purifying process is calculated based on the method of 1mm of initial loss and 1mm of later loss.
Besides the method for acquiring and selecting the unit line based on the segmentation base flow, the application also provides two methods of directly algebraically solving the unit line and calculating the unit line based on the distributed drainage basin.
Method 1: direct algebraic solution of unit line
Q 0 ＝P 0 ·u 0
Q 0 ＝P 0 ·u 1 +P 1 ·u 0
Q 0 ＝P 0 ·u 2 +P 1 ·u 1 +P 2 ·u 0
Q 0 ＝P 0 ·u 3 +P 1 ·u 2 +P 2 ·u 1 +P 3 ·u 0
……
Wherein: q is the runoff course of the basin or subinterval; p is the corresponding rain-purifying process; u is a unit line. According to the measured data, the value of the unit line can be obtained if the equation set is solved in turn.
Compared with the method provided by the application, the direct algebraic solution algorithm is convenient to calculate, and has the obvious defects of strong error transmissibility, and Qi or Pi in any period can be sequentially transmitted when errors exist, so that the unit line has a saw tooth shape or even a negative value. And when the rainfall period is more (more than 3 segments, for example), the calculation steps are more, and the error transfer phenomenon is more obvious. The more rainfall periods, the more loose the assumed multiple ratio relationship between rainfall and runoff is, and the more difficult it is to obtain reasonable unit line achievements. In actual work, the method can solve the rain and flood data of a unit line by using a direct algebraic method, so that the actual utilization rate of the method is low.
Method 2: distributed watershed feature based computation
a) And calculating a unit line based on a plurality of rainfall-runoff processes, and increasing the reliability of the forecast in application.
b) For each flood, calculating the total current coefficient of the flood according to the following formula:
wherein: a is the area of the river basin, Q is the measured flow rate, and P is the measured precipitation.
c) And calculating the flow production process according to the actually measured rainfall process and the flow production coefficient alpha of the whole field flood.
d) Assuming a unit flow rate constant K v Sum cell outflow coefficient K L The cell flow rates were calculated according to the following formula:
wherein: s is the unit grade and V is the flow rate. And calculating the process of collecting the product flow of each unit to an outlet point according to the flow rate of each distributed unit in the water collecting interval. And obtaining the runoff calculating process of the outlet end face according to the linear superposition principle.
e) Repeating step d by automatic optimization algorithm (such as SCE, SCE-UA, ARS, DREAM, etc.) until the runoff process of all field floods is best line-fitted with the measured runoff process, and further optimizing the confluence parameter K of the river basin v And K L 。
f) And assuming that the runoff with unit depth exists on the drainage basin, calculating a unit line corresponding to the drainage basin by utilizing the optimized converging parameters.
In the unit line calculation and calculation method based on the distributed drainage basin characteristics, the accuracy of the drainage basin characteristics influences the accuracy of the unit line.
The above embodiments are merely preferred embodiments of the present application, the protection scope of the present application is not limited thereto, and any simple changes or equivalent substitutions of technical solutions that can be obviously obtained by those skilled in the art within the technical scope of the present application disclosed in the present application belong to the protection scope of the present application.
Claims (10)
1. The river basin conflux unit line deducing method based on the dividing base flow is characterized by comprising the following steps:
selecting a water collecting area or a subinterval, and selecting a site with precipitation data in the water collecting area or the subinterval origin-destination time period by a Thiessen polygon method;
obtaining a precipitation data sequence with equal time intervals through an accumulation interpolation method based on precipitation data of the station;
judging site weights according to the precipitation data sequences of the water collecting interval or the subinterval, and obtaining a surface average precipitation sequence after weighting and averaging the weights of all sites in the water collecting interval and the subinterval;
acquiring a rain purifying process based on the surface average precipitation sequence;
judging a starting point and an ending point of the base flow segmentation according to a rain purifying process and a flow generating process, and obtaining the base flow process by using a linear interpolation method based on the starting point and the ending point of the base flow segmentation;
setting a triangle unit line as an initial value unit line on the basis of basic flow segmentation;
and carrying out local optimization on the initial value unit line by adopting an ant colony algorithm, and deducing the unit line after local optimization.
2. The method for estimating the flow field convergence unit line based on the split base flow according to claim 1, wherein after the water collecting area or the subinterval is acquired, field flood data is selected, after the outlet site of the flood is determined, no control site is selected or not selected at the upstream, and the research range is the water collecting area from the outlet site to the water diversion ridge;
after determining the exit site, one or more control sites are upstream and selected, and the scope of investigation is a subinterval above the exit site and below the upstream control site.
3. The method for estimating the flow field confluence unit line based on the split base flow as claimed in claim 2, wherein the step of obtaining the flow generating process comprises the following steps:
calculating the confluence process of flood branches to the sections of the outlet sites by using a Ma Sijing heel method;
and subtracting the data after the flood tributaries are converged by using the measured data of the outlet station to obtain the stream production data, and obtaining the stream production process according to the stream production data.
4. The method for calculating the drainage basin converging unit line based on the split base flow according to claim 2, wherein when the net rain process is calculated based on the surface average precipitation sequence, the water loss is divided according to the method of 1mm of initial loss and 1mm of later loss, and the net rain process of each field flood is obtained.
5. The method for estimating a flow-area confluence unit line based on a division base flow according to claim 2, wherein a triangle unit line is set as an initial value unit line based on the division of the base flow, and the initial value unit line comprises the following parameters:
peak value, which is the measured flood peak divided by the net rainfall;
the rising time period number is rising time-rainfall start time;
the number of the flood period is peak time-rainfall start time;
the total duration of the unit line is the total time of flood diversion and the rainfall start time.
6. The method for estimating a drainage basin conflux unit line based on a split base stream according to claim 5, wherein the triangle unit line comprises four control parameters, specifically:
triangle endpoint: iEnd, the minimum value is 1, and the maximum value is the total time period length of the selected flood;
triangle vertex abscissa: iMid, minimum value is 1, maximum value is 2/3 of iEnd;
triangle starting point: iBeg, minimum value is 0, maximum value is iMid;
triangle peak: uMax, minimum is 0 and maximum is Qmax/Pmax for the next flood.
7. The method for estimating a drainage basin conflux unit line based on a split base stream according to claim 6, wherein obtaining the triangle unit line comprises the steps of:
the triangular unit line is obtained by using the SCE-UA algorithm, taking the four control parameters as selection objects, taking Nash efficiency coefficient as a selection index, taking total error <100% and peak time error <10 as boundary conditions, and taking improvement rate of two selection results before and after <0.01 as exit conditions.
8. The method for estimating a drainage basin conflux unit line based on a split base stream according to claim 1, wherein the initial value of three elements of the unit line is preferably set by using an ARS algorithm with the initial value of the unit line and with NSCE closest to 1 as a target.
9. The method for estimating the drainage basin conflux unit line based on the split base stream according to claim 1, wherein the locally optimizing the initial value unit line by adopting the ant colony algorithm comprises the following steps:
and (3) constructing judgment indexes:
wherein: q (Q) oi Is the measured flow; q (Q) ci The flow is simulated by using an initial value unit line;
for each value u of the unit line u i Respectively calculating corresponding judgment indexes e after correction of +/-1% i+ And e i- ；
Replacing the original judgment index by utilizing the correction which improves the judgment index to the maximum extent, acquiring a new initial value, and sequentially iterating until the correction of the judgment index is smaller than the error line;
the logarithmic value is negative value u i First, the correction is carried out to the value u i Half of the former value, i.e. 0.5u i-1 ；
For adjacent values u after negative values i+1 First, correcting the value to be adjacent value u i+1 Half of (1), i.e. 0.5u i+1 ；
The ant colony algorithm is utilized, n or n+1 unit lines are taken as selection objects, half of deterministic coefficient and peak value error is taken as selection indexes, total error <50%, peak time error < = 1 are taken as boundary conditions, improvement rate of two selection results before and after is taken as exit conditions, and the unit lines after local optimization are obtained.
10. The method for estimating the drainage basin conflux unit line based on the split base stream according to claim 1, wherein the unit line after the local optimization is convolved with the net rain process to obtain the simulation data of the runoff process.
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