A hydrological coupling simulation system and method

Abstract

The application relates to the technical field of water resource management, in particular to a hydrological coupling simulation system and method. The method comprises the following steps: collecting long-term flow data of a first tributary and a second tributary in a target reservoir; obtaining the inflow and outflow data of a control reservoir upstream of the first tributary and the second tributary, and calculating the storage influence quantity of the control reservoir; restoring the long-term flow data by using the storage influence quantity to obtain an inflow sequence; calculating the runoff vector component of the inflow sequence to determine the concentration degree representing the runoff concentration degree of the first tributary and the second tributary and the concentration period representing the runoff concentration time; and synchronously quantifying the runoff intra-annual uneven distribution coefficient of the inflow sequence. The application realizes high-precision and evolvable simulation of the runoff process of a basin under the synergistic action of multiple tributaries by introducing vector runoff modeling and dynamic tributary contribution rate adjustment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water resources management, and particularly relates to a hydrological coupling simulation system and method. BACKGROUND

[0002] The hydrological system of a reservoir into which two tributaries flow generally has complex runoff coupling effects. The two tributaries with different properties form a complex water flow intersection mode near the confluence point. One tributary may carry a large amount of sediment, be turbid and have a large density; the other tributary may be relatively clear and have a small density. The density difference causes stratified flow in the confluence area.

[0003] The existing hydrological simulation method generally adopts the idea of independent analysis of a single tributary. This method regards each tributary as an independent hydrological unit, calculates the runoff characteristics and hydrological parameters of each tributary, and then simply superimposes them to obtain the total inflow of the reservoir. However, this simplified processing method ignores the complex hydrological interaction mechanism between the tributaries. In fact, when multiple tributaries converge at the reservoir, significant coupling effects occur, including mutual interference of flow velocity fields, mutual influence of sediment transport, and mutual adjustment of runoff time distribution. These coupling effects directly affect the water quality of the reservoir, the sediment deposition mode and the effectiveness of the flood control scheduling strategy. SUMMARY

[0004] Therefore, it is necessary to provide a hydrological coupling simulation system and method to solve at least one of the above technical problems.

[0005] To achieve the above-mentioned purpose, a hydrological coupling simulation method is applied to a hydrological system including two tributaries flowing into a target reservoir. The hydrological system includes a first tributary, a second tributary and a target reservoir. The method includes the following steps:

[0006] Step S1: collecting long-term flow data of the first tributary and the second tributary into the target reservoir; obtaining the inflow and outflow data of the upstream control reservoir of the first tributary and the second tributary, and calculating the storage effect of the upstream control reservoir; and restoring the long-term flow data by using the storage effect to obtain an inflow sequence;

[0007] Step S2: calculating the runoff vector component of the inflow sequence to determine the concentration degree representing the concentration degree of the runoff of the first tributary and the second tributary and the concentration period representing the concentration time of the runoff; and quantifying the runoff intra-annual uneven distribution coefficient of the inflow sequence synchronously;

[0008] Step S3: determining the flood period and the dry period of the current year based on the concentration period; calculating the preliminary dry-branch contribution rate of each tributary in the flood period and the dry period by using the inflow sequence; and correcting the preliminary dry-branch contribution rate by using the runoff intra-annual uneven distribution coefficient to obtain the dry-branch contribution rate.

[0009] Step S4: taking the concentration, runoff intra-annual distribution uneven coefficient and pre-calculated extreme value ratio as the judgment basis of extreme event intensity, determining strong extreme hydrological events and analyzing the persistence impact characteristics;

[0010] Step S5: statistically analyzing the concentration, concentration period and dry-branch contribution rate of the historical years, taking the concentration, concentration period and dry-branch contribution rate of the historical years as independent variables, linearly analyzing the change trend of the long-term inflow composition of the target reservoir, and adjusting the double-branch coupling basin runoff simulation result according to the persistence impact characteristics of the current year.

[0011] The application also provides a hydrological coupling simulation system for executing the hydrological coupling simulation method as described above, and the hydrological coupling simulation system comprises:

[0012] The flow recovery module is configured to collect long-term flow data of the first branch and the second branch entering the target reservoir, acquire the inflow and outflow data of the upstream control reservoir of the first branch and the second branch, and calculate the regulation and storage influence amount of the upstream control reservoir; and the long-term flow data is restored by using the regulation and storage influence amount to obtain an inflow sequence.

[0013] The runoff structure analysis module is configured to calculate a runoff vector component of the inflow sequence to determine a concentration representing the concentration degree of the first branch and the second branch and a concentration period representing the concentration time; and the runoff intra-annual distribution uneven coefficient of the inflow sequence is quantified synchronously.

[0014] The dry-branch contribution rate module is configured to determine the flood period and the dry period of the current year based on the concentration period; calculate the preliminary dry-branch contribution rate of each branch in the flood period and the dry period through the inflow sequence; and the preliminary dry-branch contribution rate is weighted and corrected by using the runoff intra-annual distribution uneven coefficient to obtain the dry-branch contribution rate.

[0015] The extreme event identification module is configured to take the concentration, runoff intra-annual distribution uneven coefficient and pre-calculated extreme value ratio as the judgment basis of extreme event intensity, determine strong extreme hydrological events and analyze the persistence impact characteristics.

[0016] The coupling trend simulation module is configured to statistically analyze the concentration, concentration period and dry-branch contribution rate of the historical years, take the concentration, concentration period and dry-branch contribution rate of the historical years as independent variables, linearly analyze the change trend of the long-term inflow composition of the target reservoir, and adjust the double-branch coupling basin runoff simulation result according to the persistence impact characteristics of the current year.

[0017] The hydrological coupling simulation method provided by the application faces a complex hydrological system of double tributaries converging into a target reservoir, constructs a complete simulation framework integrating flow recovery, vector analysis, dry and tributary contribution rate modeling, extreme event identification and trend prediction, and realizes fine description and dynamic regulation of the basin inflow process. The method first sets up water level gauges, flowmeters, rain gauges and other monitoring equipment, combines with the reservoir capacity change to compensate the measured flow, accurately restores the real inflow sequence, and ensures that the data basis has high timeliness and accuracy. In terms of flow structure analysis, the method constructs a runoff vector model through month angle mapping and vector component calculation, which can quantitatively reflect the concentration degree (concentration degree) and main inflow period (concentration period) of the tributaries. Compared with the traditional average value or total amount analysis, the model can reveal the time shift and concentration trend of the tributary inflow characteristics in the year, and provide a scientific basis for subsequent water period division.

[0018] After dividing the flood period and dry period based on the concentration period, the method further constructs the dry and tributary interaction factor through the flow dominance ratio, sediment concentration ratio and exponential decay factor, and combines the uneven annual distribution coefficient to weight correct the preliminary dry and tributary contribution rate, so that the dry and tributary contribution calculation more comprehensively reflects the dynamic coupling relationship between the water quantity and material transport process, especially in the area where the flood and dry water conversion is obvious, which shows higher adaptability and stability.

[0019] In the aspect of extreme event identification, the method constructs an extreme event intensity index integrating concentration degree, uneven coefficient, annual and historical extreme value ratio, accurately identifies abnormal hydrological years, and further analyzes the persistent influence of the abnormal hydrological years on the inflow structure, to provide dynamic correction conditions for prediction. By constructing the concentration degree, concentration period and dry and tributary contribution rate in the historical data into a linear regression equation, the change trend is extracted, and the extreme influence characteristics of the current year are introduced to adjust the slope, to realize the unified modeling of trend prediction and sudden response.

[0020] The method not only improves the accuracy and explanatory power of the basin inflow simulation, but also has strong expandability, which can be used in water resources scheduling optimization, climate change hydrological response analysis and extreme hydrological event emergency prediction, and has the potential to be integrated into a real-time monitoring system, to provide technical support for future fine management of the basin. BRIEF DESCRIPTION OF DRAWINGS

[0021] Other features, objects and advantages of the application will become more apparent from the following detailed description of non-limiting embodiments made with reference to the accompanying drawings:

[0022] Figure 1 A step flowchart of the hydrological coupling simulation method applied in the application is provided;

[0023] Figure 2 A basin runoff annual distribution box plot provided by an embodiment of the application is provided.

[0024] Figure 3 A monthly runoff distribution process column chart provided by an embodiment of the present application;

[0025] Figure 4 A runoff concentration degree change chart of a river basin provided by an embodiment of the present application;

[0026] Figure 5 A runoff concentration period change chart of a river basin provided by an embodiment of the present application;

[0027] Figure 6 A runoff unevenness coefficient change chart of a river basin provided by an embodiment of the present application. DETAILED DESCRIPTION

[0028] The technical method of the present application will be described clearly and completely in combination with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0029] In addition, the accompanying drawings are only schematic illustrations of the present application, and are not necessarily drawn to scale. The same reference numerals in the drawings represent the same or similar parts, and thus repeated description thereof will be omitted. Some block diagrams shown in the drawings are functional entities, and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0030] It should be understood that although the terms "first", "second" and the like can be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, without departing from the scope of the exemplary embodiments, a first element can be referred to as a second element, and similarly a second element can be referred to as a first element. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0031] To achieve the above-mentioned purpose, please refer to Figures 1 to 6 The present application provides a hydrological coupling simulation method applied to a hydrological system comprising a double tributary merging into a target reservoir, the hydrological system comprising a first tributary, a second tributary and a target reservoir, the method comprising the following steps:

[0032] Step S1: Collect long-term flow data of the first branch stream and the second branch stream at the target reservoir inlet; obtain the inflow and outflow data of the upstream control reservoir of the first branch stream and the second branch stream, and calculate the storage influence of the upstream control reservoir; restore the long-term flow data using the storage influence to obtain the inflow flow sequence;

[0033] In some embodiments, to collect long-term flow data of the first branch stream and the second branch stream at the target reservoir inlet, first, hydrological monitoring equipment is arranged at the key control section of the two branch streams near the reservoir, including radar water level gauge, ultrasonic Doppler flowmeter and tipping bucket rain gauge. The water level gauge and flowmeter are installed at a position about 1.5 times the river width away from the section, perpendicular to the main flow direction, to improve measurement accuracy and reduce local turbulence interference. At the same time, through the hydrological data sharing platform or special data interface, the inflow and outflow data of the upstream control reservoir of the first branch stream and the second branch stream are obtained. The upstream control reservoir includes but is not limited to each level of reservoir in cascade development, regulating reservoir and water storage project, etc., and the specific control reservoir range is determined according to the actual basin situation. Based on the obtained inflow and outflow data of the upstream control reservoir, the storage influence of each reservoir in the calculation period is calculated. The storage influence reflects the degree of change of the upstream reservoir regulation operation on the downstream natural runoff process, and through the influence, the flow data affected by the regulation can be restored to the runoff process close to the natural state.

[0034] In some embodiments, the collection frequency is set to every 10 minutes, and the monitoring data is uploaded to the control center database of the target reservoir in real time through 4G or GPRS network.

[0035] Step S2: Calculate the runoff vector component of the inflow flow sequence to determine the concentration degree representing the concentration degree of the first branch stream and the second branch stream and the concentration period representing the concentration time of the runoff; simultaneously quantify the runoff inter-annual distribution uneven coefficient of the inflow flow sequence;

[0036] In some embodiments, to further reveal the concentration characteristics of the first tributary and the second tributary in time, the runoff vector component calculation process is needed for the inflow sequence. The specific component process is as follows: the annual inflow data is classified by month, and the average monthly flow is calculated. The flow value of each month is projected onto the X axis (vertical direction) and the Y axis (horizontal direction) respectively, and 12 X components and 12 Y components are obtained. The sum of the X components of the 12 months is the annual vertical runoff vector, and the sum of the Y components is the horizontal runoff vector. The total length of the runoff vector is calculated after the two are combined, and the ratio of the length to the annual total runoff is defined as the concentration degree, which represents the concentration degree of the annual flow. The angle corresponding to the direction of the vector combination (considering the positive and negative signs) is defined as the concentration period, which represents the period in which the maximum flow concentration occurs in a year. At the same time, the variance of the flow value of the 12 months is normalized to the average value to obtain the runoff uneven distribution coefficient within a year. The coefficient ranges from 0 to 1, and the larger the value, the more uneven the water distribution within a year.

[0037] It should be noted that the time vectorization idea described above is as follows: assuming that each month represents an angle position, where January is 0 degrees, each month increases by 30 degrees clockwise, and December corresponds to 330 degrees.

[0038] Step S3: determining the flood period and dry period of the current year based on the concentration period; calculating the preliminary main-tributary contribution rate of each tributary in the flood period and the dry period based on the inflow sequence, and correcting the preliminary main-tributary contribution rate by using the runoff uneven distribution coefficient within a year to obtain the main-tributary contribution rate;

[0039] In some embodiments, the concentration period information is utilized to extend it by 45 degrees forward and backward, respectively, corresponding to form a 90-degree hydrological time interval as the flood period of the year. According to the mapping relationship between the month and the angle, the angle interval is converted into the actual month, for example, if the concentration period is 150 degrees, the flood period is from the middle of April to the middle of July; the rest of the months are determined as the dry period. Then the total flow of the two tributaries in the flood period and the dry period is respectively summarized, the ratio of the difference value of the flow of the two tributaries in the flood period to the total flow is calculated, and the flow dominance ratio is obtained; then multiplied by the preset annual average sediment concentration ratio of the two tributaries, the flood period interaction factor is obtained, which is used to represent whether the high-flow tributary is also a high-sediment tributary. The calculation method of the dry period interaction factor is to take the natural logarithm of the ratio of the second tributary flow to the first tributary flow in the dry period, and multiply it by an exponential decay function, which takes e as the base number, and the index is the negative value of the product of the geomorphic attenuation coefficient k and the duration of the dry period, reflecting the weakening trend of the flow dominance in the long-term dry period. The flow of each tributary in the flood period is divided by the total flow in the flood period, and multiplied by (1 plus the interaction factor), to obtain the preliminary dry-branch contribution rate; in the dry period, it is also divided by the total flow and multiplied by (1 minus the absolute value of the interaction factor), so as to obtain the preliminary dry-branch contribution rate. Finally, combined with the uneven coefficient, the maximum correction amplitude is set, the correction strength is calculated according to the difference between the uneven coefficient and the threshold value 0.7 (standardized processing is adopted by using Sigmoid function), and the preliminary contribution rate is corrected to form the final dry-branch contribution rate.

[0040] Step S4: Taking the concentration degree, runoff intra-annual distribution uneven coefficient and pre-calculated extreme value ratio as the judgment basis of extreme event intensity, strong extreme hydrological events are determined and the persistent influence characteristics are analyzed;

[0041] In some embodiments, according to the inflow flow sequence and the analysis results, whether there is a strong extreme hydrological event in the current year is determined. The ratio of the maximum monthly average flow to the minimum monthly average flow in the 12 months of the year is calculated to obtain the intra-annual extreme value ratio; then the ratio of the maximum annual total flow to the minimum annual total flow in the historical multi-year data is calculated to obtain the historical extreme value ratio. Then, the concentration degree, the intra-annual distribution uneven coefficient and the two extreme value ratios are combined to construct an extreme event intensity index, and the calculation structure is the product of the four factors divided by the normalization constant K. If the index exceeds the empirical threshold value, it is determined that the year is a strong extreme hydrological year. Then the persistent influence on the inflow structure is analyzed, combined with the characteristics of concentration period delay or concentration degree enhancement, the influence trend of the extreme process on the subsequent seasonal hydrological structure is evaluated.

[0042] It should be noted that the normalization constant K defaults to 2.0 for plain areas and 1.0 for karst areas, which is a continuous parameter dynamically configured according to landform types, representing the amplification / inhibition effect of landform on extreme events. Note that this does not cover all landform treatments. If no specific landform type is identified, use the weighted integrated K value: K = 0.3 x K 喀斯特 + 0.7 x K 平原 = 0.3 x 1.0 + 0.7 x 2.0 = 1.7; it also supports inputting K value through hydrological database interface (e.g. K = 1.2 for volcanic rock area).

[0043] Step S5: Statistically analyze the concentration, concentration period and contribution rate of the historical years, and adjust the results of the dual-stream coupling runoff simulation according to the persistence characteristics of the current year.

[0044] In some embodiments, the statistical concentration, concentration period and contribution rate data are traced back to a series of 30 years or more, forming three independent time series. Linear regression models are established for the concentration trend, concentration period drift trend and dry-branch structure change trend, respectively, with year as the independent variable. The regression slope and intercept are extracted, with the intercept representing the hydrological baseline characteristics and the slope representing the speed of hydrological change trend. Thereafter, combined with the intensity of the extreme event determined in the current year, if it is a strong extreme year, the trend slope is amplified by multiplying a strengthening coefficient in the range of 1.5 to 2.0; if it is a weak impact year, the trend slope is weakened by multiplying a decay factor less than 1. Finally, on the basis of the existing trend, short-period disturbance adjustment is realized, forming the dynamically corrected dual-stream coupling inflow simulation results, which can be applied to hydrological regulation, inflow prediction and risk management in the current year or future years, especially for mountainous reservoirs controlled by dual streams or monsoons.

[0045] Further, step S1 includes the following steps:

[0046] Step S11: Install water level meters, flow meters and rain gauges at the inflow section of the target reservoir for the first stream and the second stream, and set fixed monitoring piles at a distance of 1.5 times the river width from the inflow section, so that the water level meters, flow meters and rain gauges are perpendicular to the water flow direction;

[0047] In some embodiments, to achieve accurate long-term monitoring of the first tributary and the second tributary inflow into the reservoir, the inflow control section of the two tributaries is selected near the main dam of the target reservoir, and the hydrological automatic monitoring equipment is arranged at the site. The water level meter, flow meter and rain gauge are arranged on each inflow section, wherein the water level meter is a non-contact radar water level meter installed on the fixed monitoring pile above the center of the section, which is used to obtain high-frequency water level information; the flow meter is an ultrasonic Doppler flow profiler, which is arranged near the riverbed on both sides of the section, used to collect multi-layer flow velocity information and automatically calculate the cross-sectional area of the flow, and then calculate the instantaneous flow; the rain gauge is arranged at a stable elevation on the shore to record the local rainfall intensity synchronously. To ensure the representativeness and stability of the observation data of the equipment, a fixed monitoring pile is set at a position about 1.5 times the river width upstream of each inflow section, and the observation equipment is arranged perpendicular to the mainstream direction of the river to avoid interference of the equipment by water flow deviation and ensure that the observation data is consistent with the true flow direction.

[0048] It should be noted that the monitoring points should be set away from sharp bends, backwater sections or water flow branch areas to ensure that the hydrodynamic structure is as uniform and stable as possible.

[0049] Step S12: Collect water level, flow velocity and rainfall data at a preset time interval using the water level meter, flow meter and rain gauge, and transmit them to the data center of the control reservoir through the 4G / GPRS network as long-term flow data; at the same time, obtain the inflow and outflow data of the upstream control reservoir of the first tributary and the second tributary;

[0050] In some embodiments, the water level meter, flow meter and rain gauge are arranged to continuously and uninterruptedly collect data at the inflow section of the two tributaries. The system uses a unified clock management, sets the sampling period to be once every 10 minutes to ensure the time sequence accuracy of the data, and the collected data includes the average water level of the section, the layered flow velocity and the cumulative rainfall, etc. The monitoring equipment has local data caching and power redundancy guarantee mechanism to ensure that it can still run continuously and save data in the case of communication exception or power failure.

[0051] At the same time, the inflow and outflow data of the upstream control reservoir of the first tributary and the second tributary are obtained in real time through the hydrological data sharing platform or the special communication interface. All monitoring equipment accesses the data center through the 4G or GPRS module, automatically transmits through the specially designed data gateway, and stores the transmission data after encryption. The data is automatically preprocessed, verified and formatted by the edge collection controller, and is classified and stored according to the inflow section number and the upstream reservoir number, to finally form a complete time series hydrological data set.

[0052] It should be noted that the flow rate data collected needs to be solved according to the flow rate-section area relationship in the flow calculation process, and the water level data is used to judge abnormal water regime events and the degree of reservoir backwater disturbance, and the rainfall data can assist in identifying rainfall runoff processes. The upstream control reservoir inflow and outflow data are used to calculate the regulation impact.

[0053] Step S13: calculating the regulation impact of the upstream control reservoir, wherein the regulation impact = outflow - inflow + reservoir capacity change amount / calculation period length; the regulation impact is used to compensate for the influence of the upstream control reservoir regulation on the long-term flow data, and the inflow sequence is obtained.

[0054] In some embodiments, in order to eliminate the influence of the upstream control reservoir regulation on the target reservoir inflow, the regulation impact of each upstream reservoir needs to be calculated. The upstream control reservoir inflow and outflow data of the first tributary and the second tributary are obtained, the regulation impact of each reservoir in the calculation period is calculated, and the regulation impact = upstream reservoir outflow - upstream reservoir inflow. For each tributary, the regulation impact of the upstream control reservoir of the tributary is superimposed on the measured flow data of the tributary at the target reservoir inflow section, and the restoration calculation is performed: the restored inflow = measured flow + regulation impact. Through the calculation process, the inflow sequence reflecting the natural runoff process can be obtained.

[0055] It should be noted that when the regulation impact is positive, it indicates that the upstream reservoir is in the state of storing water, and the actual natural inflow is greater than the observed flow; when the regulation impact is negative, it indicates that the upstream reservoir is increasing the outflow, and the actual natural inflow is less than the observed flow. The restoration calculation process is automatically completed by the hydrological data processing system, ensuring the consistency and accuracy of data processing.

[0056] Please refer to Figure 2 The annual distribution box plot of the basin runoff provided by an embodiment of the present application and Figure 3 The monthly runoff distribution process column chart provided by an embodiment of the present application is shown by Figure 2 It can be seen that the annual distribution process of the A reservoir basin runoff in a certain region presents an "asymmetric single-peak type" distribution. Figure 3 The average monthly runoff of the A reservoir basin accounts for the annual runoff ratio, as shown by Figure 3It can be seen that the maximum monthly runoff of the A reservoir basin occurs in June, July and August, accounting for 16.27%, 20.12% and 17.22% of the annual runoff; the minimum monthly runoff occurs in March, accounting for 2.35% of the annual runoff; the maximum monthly runoff is 6.94, 8.57 and 7.34 times of the minimum monthly runoff, respectively; the continuous maximum four-month runoff occurs from June to September, accounting for 66.20% of the annual runoff; the continuous minimum four-month runoff occurs from January to April, accounting for 10.40% of the annual runoff. The above data all show that the annual distribution of runoff in the A reservoir basin is extremely uneven.

[0057] Further, the runoff vector components of the reservoir inflow sequence are calculated in step S2 to determine the concentration degree representing the concentration degree of the runoff of the first branch and the second branch and the concentration period representing the concentration time of the runoff, which are specifically:

[0058] The reservoir inflow sequence is grouped by month to calculate the monthly average flow value of each month, and a corresponding angle coordinate is assigned to each month, wherein January corresponds to 0 degrees, each month increases by 30 degrees, and December corresponds to 330 degrees as the central angle of the month;

[0059] The runoff vector components of the first branch and the second branch in the X axis and Y axis directions are calculated respectively, wherein the component value is calculated by the formula:

[0060]

[0061] In the formula, R x is the sum of the vertical component of the runoff vector component in the X axis, r i is the monthly average flow value of the i-th month, θ i is the central angle of the i-th month, R y is the sum of the horizontal component of the runoff vector component in the Y axis;

[0062] The runoff vector components are used to determine the concentration degree representing the concentration degree of the runoff of the first branch and the second branch and the concentration period representing the concentration time of the runoff.

[0063] Further, the runoff vector components are used to determine the concentration degree representing the concentration degree of the runoff of the first branch and the second branch and the concentration period representing the concentration time of the runoff, which are specifically:

[0064] The synthetic length of the runoff vector components of the first branch and the second branch is calculated respectively, wherein the synthetic length is

[0065] The runoff vector components are used to calculate the concentration degree representing the concentration degree of the runoff of the first branch and the second branch, wherein the concentration degree = synthetic length / total runoff in the study period;

[0066] When the sum of the runoff volume horizontal components of the runoff vector components on the Y-axis is greater than zero, the concentration period is arctan(R x / R y );

[0067] When the sum of the runoff volume horizontal components of the runoff vector components on the Y-axis is less than zero, the concentration period is arctan(R x / R y )+180°;

[0068] When the sum of the runoff volume horizontal components of the runoff vector components on the Y-axis is equal to zero, and the sum of the runoff volume vertical components of the runoff vector components on the X-axis is greater than zero, the concentration period is 90°;

[0069] When the sum of the runoff volume horizontal components of the runoff vector components on the Y-axis is equal to zero, and the sum of the runoff volume vertical components of the runoff vector components on the X-axis is less than zero, the concentration period is 270°.

[0070] In some embodiments, in order to analyze the characteristics of the first tributary and the second tributary from the time structure of the inflow process, the runoff vector component calculation is performed on the long-term inflow sequence to extract two key indicators: runoff concentration degree (concentration degree) and runoff concentration time (concentration period). To this end, the runoff vector component of the inflow sequence needs to be calculated:

[0071] The inflow sequence of the first tributary and the second tributary is grouped and counted by month respectively, and the counting method is to average the inflow of all time steps (such as daily, hourly) in each month of each year to obtain the monthly average flow value, a total of 12 values, respectively r1 to r 12 In order to make each month have an independent angle coordinate on the circular vector diagram, a unique central angle is assigned to each month, with January set to 0 degrees, February to 30 degrees, and so on, to 12 months to 330 degrees, forming a set of 360-degree full-coverage month angle coordinates θ1 to θ 12 .

[0072] After obtaining the flow of each month and its corresponding angle, the flow of each month is regarded as the vector intensity in that direction, and is projected onto the X-axis (horizontal) and Y-axis (vertical) directions, and the resultant components of all vectors in the X-axis and Y-axis directions are calculated. The calculation method of the X-axis component R x is to multiply the monthly flow r i by the sine value sin(θ i ) of the monthly angle θ i , and accumulate 12 months, that is, R x =r1·sin(θ1)+r2·sin(θ2)+…+r 12 ·sin(θ 12) ; Y-axis component R γ is r1cos(θ1) + r2cos(θ2) +... + r 12 cos(θ 12 ). Wherein, the input angle θ i of sin and cos must be converted to radian system to adapt to the mathematical function processing in the computing system.

[0073] After the above vector component calculation, R x and R γ are composed as two components in the rectangular coordinate system to synthesize the runoff vector. The modulus of the vector, i.e. the synthetic length, reflects the intensity of the resultant vector formed by the annual runoff in the time distribution. The greater the synthetic length, the more concentrated the flow is in a certain period. To further quantify the concentration degree, the synthetic length is divided by the total runoff ∑r i of the study year or years, and the concentration degree index is obtained to measure the concentration of runoff time distribution. The closer the value is to 1, the more the flow is concentrated in a few periods; the closer the value is to 0, the more uniform the flow distribution is.

[0074] In order to calculate the concentration period, i.e. the month position pointed by the direction of the synthetic vector, the positive and negative sign combination of R x and R y is determined to determine the quadrant of the direction angle. If R y > 0, the concentration period angle is arctan(R x / R y ); if R y < 0, the concentration period angle needs to be added by 180 degrees to ensure that the direction falls in the third or fourth quadrant; if R y = 0 and R x > 0, the concentration period angle is 90 degrees; if R y = 0 and R x < 0, the concentration period angle is 270 degrees, and the concentration period can be accurately deduced according to the quadrant where R x , R y falls. Finally, the angle value can be converted into the corresponding month, and the corresponding concentration month can be obtained by dividing the angle by 30°, for example, the concentration period angle is 150°, and the main runoff period falls around June.

[0075] It should be noted that the standard arctan(R x / R y) The range of the function is only (-90°, 90°), which can only cover the angles in the first quadrant (0°-90°) and the fourth quadrant (270°-360°). If this formula is used directly, the calculation result will be incorrectly mapped to the fourth or first quadrant when the synthetic vector is located in the second or third quadrant, resulting in a half-year (180° corresponds to 6 months) time deviation of the concentration period.

[0076] It should be noted that when calculating the concentration period using the arctangent function, an arctangent variant function with a signed judgment function (such as atan2) should be used to avoid angle deviation caused by zero denominator or sign error; at the same time, the dimensions of the synthetic length and the total flow amount must be consistent to ensure that the concentration is a dimensionless ratio. In addition, this method can be widely used for hydrological characteristic comparison and analysis of multiple tributaries or entire basins, and has good visual interpretation power, which can directly display the hydrological time offset characteristics of different tributaries on a polar coordinate graph, providing a basis for modeling of basin water resources space-time regulation and dry-branch relationship.

[0077] Referring to Figure 4 The concentration value of the runoff of the A reservoir basin in the same region from 1971 to 1983 has a large variation range, between 0.31 and 0.66, and the annual distribution concentration of the runoff of the A reservoir basin has a large variation between years; the concentration value of the runoff of the A reservoir basin from 1983 to 2010 has a small variation range, between 0.38 and 0.63, and the annual distribution concentration of the runoff of the basin has a small variation between years; the concentration value of the runoff of the A reservoir basin from 2020 to 2023 has a small variation range, around 0.45, indicating that the annual distribution concentration of the runoff of the A reservoir basin from 2020 to 2023 is low. The linear trend of the sequence of the annual concentration coefficient of the runoff in many years is decreasing, which indicates that the rainfall concentration of the runoff of the A reservoir basin will tend to decrease.

[0078] Referring to Figure 5 The concentration period of the runoff of the A reservoir basin in the same region from 1957 to 2023 is distributed in June, July and August, among which July and August account for 41% and 58% of the years as the annual runoff concentration period in 67 years, respectively, and only in 2022 and 2011 is the runoff concentration period in June. From the sequence of many years, the runoff concentration period of the A reservoir basin since 1957 has shown a certain decreasing trend, which indicates that the date of the maximum value of the annual runoff of the A reservoir basin has a trend of advancing.

[0079] Further, the formula for quantifying the runoff annual distribution unevenness coefficient of the reservoir inflow sequence in step S2 is specifically:

[0080]

[0081] In the formula, C v is the uneven distribution coefficient of runoff in the year, the value range is between 0-1.0, n is the number of months, V i is the runoff in each month of the year, V Q is the monthly average runoff in the year.

[0082] Please refer to Figure 6 The runoff uneven coefficient variation chart provided by an embodiment of the present application is shown in the figure, for the same region, the variation range of the runoff uneven coefficient of the A reservoir basin is high from 1957 to 2000, the uneven coefficient is between 0.62-1.06, the annual distribution is frequently changed; the variation range of the runoff uneven coefficient of the A reservoir basin is low from 2001 to 2008, the uneven coefficient is between 0.65-0.79, the annual distribution is relatively uniform. The most uneven annual distribution year of the runoff of the A reservoir basin is 1979, and the most uniform annual distribution years are 1972, 2013 and 2016. The linear trend of the runoff annual distribution coefficient sequence is decreasing, which shows that the uneven state of the runoff of the A reservoir basin will develop towards the decreasing trend in the future, which is consistent with the analysis result of the concentration degree, and further verifies the runoff trend of the region.

[0083] Further, the step S3 comprises the following steps:

[0084] Step S31: taking the concentration period as the center, the angle range of 45 degrees forward and backward is determined as the flood period angle;

[0085] Step S32: the flood period angle is converted into the corresponding month time period as the flood period of the year, wherein when the angle range exceeds 0°-360°, the angle normalization processing is carried out by using the modulo 360° operation;

[0086] Step S33: the remaining months in a year except the flood period are determined as the dry period;

[0087] Step S34: the flow difference value of the first branch and the second branch in the flood period and the sum of the total flow of the double-branch flood period are calculated through the reservoir inflow sequence, the flow difference value is divided by the sum of the total flow of the double-branch flood period, and the flow dominance ratio is obtained;

[0088] Step S35: the flow dominance ratio is multiplied by the pre-acquired sediment concentration ratio of the two branches to calculate the flood period interaction factor, wherein the flood period interaction factor indicates that if the first branch flow is greater than the second branch, the factor value is positive, otherwise it is negative, and the contribution rate of the high sediment concentration branch is inhibited;

[0089] Step S36: Calculate the ratio of the second tributary dry season flow to the first tributary dry season flow through the in-flow sequence, and take the natural logarithm of the ratio and multiply it by an exponential decay term to obtain the dry season interaction factor, wherein the exponential decay term is the negative k times the dry season duration times the square of e, and k is the geomorphology decay coefficient;

[0090] Step S37: Divide the flood season flow of each tributary by the total flood season flow, and multiply it by (1 + the flood season interaction factor); divide the dry season flow of each tributary by the total dry season flow, and multiply it by (1 - the absolute value of the dry season interaction factor) to form the preliminary dry-tributary contribution rate.

[0091] Step S38: Use the runoff intra-annual distribution unevenness coefficient to weight correct the preliminary dry-tributary contribution rate to obtain the dry-tributary contribution rate.

[0092] Further, step S38 includes:

[0093] Set the maximum adjustment range of the initial dry-tributary contribution rate as the maximum correction amplitude;

[0094] Calculate the difference between the runoff intra-annual distribution unevenness coefficient and the threshold value 0.7, and record it as the unevenness difference;

[0095] Map the unevenness difference to the correction intensity coefficient based on the Sigmoid function;

[0096] Use the initial dry-tributary contribution rate, the maximum correction amplitude, and the correction intensity coefficient to calculate the dry-tributary contribution rate, wherein the dry-tributary contribution rate in the flood season = initial dry-tributary contribution rate × (1 + maximum correction amplitude × correction intensity coefficient), and the dry-tributary contribution rate in the dry season = initial dry-tributary contribution rate × (1 - maximum correction amplitude × correction intensity coefficient).

[0097] In some embodiments, in order to quantitatively analyze the dominant contribution of the double tributaries to the runoff process of the controlled reservoir in different water periods, the aforementioned concentrated period information is combined to further demarcate the flood period and the dry period, with the concentrated period as the center point of the time window, and a dry-tributary contribution rate model is constructed on this basis. For example, when the concentrated period is 150 degrees, the angle range of the flood period is 105 degrees to 195 degrees. The angle range is matched with the minimum angle between each month center angle (e.g. 0 degrees in January, 30 degrees in February, and so on) to convert into the corresponding natural months, forming the flood period month segment of the year. When the angle range exceeds 360° or is less than 0°, the modulo 360° operation is used for normalization. For example, when the concentrated period is 345 degrees, the extended angle interval is 300° to 30°, and the flood period is November, December and January of the next year. The remaining months in a year that are not classified into the flood period are determined as the dry period. Then the flow of the first tributary and the second tributary in the flood period is added up to obtain the total flow of the double tributaries in the flood period, and the flow difference between the two is calculated. The difference is divided by the total flow to obtain the flow advantage ratio, which reflects the dominant degree of a tributary in the flood period. In order to comprehensively consider the correction effect of sediment content difference on the contribution of the tributary, the interaction factor in the flood period is obtained by multiplying the above-mentioned flow advantage ratio by the preset average sediment content ratio of the two tributaries. If the flow of the first tributary is greater than that of the second tributary and the sediment content is also high, the factor value is positive but the influence direction is inhibitory, that is, the weight of the high-sediment-content tributary is reduced. If the high-flow tributary has low sediment content, the factor value may be negative, which instead increases its contribution rate to reflect the synergistic effect of erosion and deposition. Then, by comparing the flow structure of the dry period, the flow ratio of the second tributary to the first tributary in the dry period is calculated, and the natural logarithm of the ratio is taken to form the dry period flow comparison basis item. Considering that the persistence of the dry period is easy to produce time decay due to geomorphic conditions, the logarithmic ratio is multiplied by an exponential decay term, which is in the form of e ―k×t), where k is the topographic attenuation coefficient and t is the number of dry season days. This term reflects that even if there is a flow difference, if the duration of the dry season is very long, the effect will be weakened due to attenuation, thus obtaining the dry season interaction factor. Combined with the above two interaction factors, the preliminary dry-branch contribution rate of each branch stream in the flood season and the dry season is calculated. The method is as follows: the flow of each branch stream in the flood season is divided by the total flow in the flood season, which is the basic proportion, and then multiplied by (1 + the flood season interaction factor) to form the preliminary dry-branch contribution rate in the flood season; the flow of each branch stream in the dry season is divided by the total flow in the dry season, and then multiplied by (1 minus the absolute value of the dry season interaction factor) to form the preliminary dry-branch contribution rate in the dry season. In this way, on the basis of ensuring water allocation, the preliminary structure relationship is formed by integrating sediment and seasonal effects. In order to improve the response ability of the dry-branch contribution rate to the fluctuation of the flow structure within a year, the runoff uneven distribution coefficient within a year is introduced for weight correction. First, set a maximum correction amplitude M, which represents the upper and lower limit adjustment proportion of the preliminary contribution rate in the most extreme case, usually set to 0.15 to 0.30. Then calculate the difference between the runoff uneven distribution coefficient within a year and the empirical threshold value 0.7, denoted as ΔC. This difference reflects the degree of skewness of the flow in the year, that is, whether it is more concentrated in a few months. Then use the Sigmoid function to map ΔC to a correction strength coefficient S between 0 and 1, which is in the form of where a is the function slope parameter, generally taking a value of 8 to 12, used to enhance sensitivity. Finally, the dry-branch contribution rate in the flood season = initial dry-branch contribution rate x (1 + M x S); the dry-branch contribution rate in the dry season = initial dry-branch contribution rate x (1 - M x S), forming the final dry-branch contribution rate result.

[0098] It should be noted that all weight adjustment processes should ensure that the results are normalized and summed to 1, and a round of proportional uniform scaling adjustment can be made after the calculation is completed to ensure water conservation. And according to the comparison chart of the dry-branch contribution rate before and after adjustment, the change process of the branch stream dominant weight under different unevenness can be observed, which provides reliable support for subsequent coupling simulation and scheduling modeling.

[0099] Further, step S4 includes the following steps:

[0100] Step S41: Calculate the ratio of the maximum monthly runoff to the minimum monthly runoff in the 12 months of the year through the reservoir inflow sequence, as the monthly extreme value ratio within a year;

[0101] Step S42: Calculate the ratio of the maximum annual runoff to the minimum annual runoff through the reservoir inflow sequence of the historical years, as the historical annual extreme value ratio;

[0102] Step S43: Calculate the extreme event intensity index according to the concentration, runoff uneven distribution coefficient within a year, monthly extreme value ratio within a year, and historical annual extreme value ratio, to obtain a strong extreme hydrological event; wherein the calculation formula of the extreme event intensity index is specifically:

[0103]

[0104] wherein RCD is the concentration degree, C v is the runoff uneven distribution coefficient within a year, R 月 is the monthly extreme value ratio within a year, R 年 is the historical annual extreme value ratio, and K is a normalization constant.

[0105] Step S44: performing a persistence impact analysis on the strong extreme hydrological event to obtain a persistence impact feature.

[0106] In some embodiments, based on the foregoing inflow sequence, concentration degree, runoff uneven distribution coefficient within a year, and other basic data, runoff extreme value information within a year and at a historical scale is further extracted, and is coupled with the concentration inflow structure to establish a composite intensity index, to assist in determining the occurrence of a strong extreme hydrological event. The specific determination process is as follows: the inflow sequence from January to December of the current year is traversed, the monthly average inflow value of each month is extracted, the maximum monthly average inflow and the minimum monthly average inflow are identified, and the ratio of the two is calculated to obtain the monthly extreme value ratio R 月 within a year. For example, if the inflow in May is the highest and the inflow in January is the lowest in a year, then R 月 = inflow in May / inflow in January, reflecting the amplitude of the inflow within a year. The higher the parameter is, the stronger the runoff concentration within a single month is, and the more intense the hydrological variability is. The total annual runoff of each year is counted, and the maximum total annual runoff and the minimum total annual runoff are identified in the sequence of the year. The ratio of the two is the historical annual extreme value ratio R 年 . This index mainly measures the fluctuation range of the hydrological regime between different years. For example, if the maximum annual runoff is twice the minimum annual runoff, then R 年 = 2, reflecting the pressure on the system to respond to runoff variability at a cross-year scale.

[0107] The concentration degree, the runoff uneven distribution coefficient within a year, the monthly extreme value ratio within a year, and the historical annual extreme value ratio are substituted into the extreme event intensity index calculation model to perform composite index fusion calculation. The model adopts a weighted multiplication superposition method, and the form is as follows: wherein K is a normalization constant.

[0108] The logic of the extreme event intensity index calculation model is as follows: when the concentration degree and the uneven distribution coefficient are high, it means that the runoff is more concentrated in time and space; R 月 and R 年 reflect the intensity of the extreme hydrological process; and the four together reflect the possibility of the system under a certain extreme hydrological structure. When the index is higher than a set threshold (such as 1.0), it is determined that a strong extreme hydrological event occurs, and the next stage of analysis is entered.

[0109] It should be noted that the relative value ratio index is used in the formula, so the unevenness caused by the absolute magnitude difference between different basins or tributaries can be automatically eliminated, and the migration generalization ability is strong.

[0110] The persistence impact analysis of the identified strong extreme hydrological event is specifically: determining whether the extreme event is formed in the flood period or the dry period; then tracking the flow trend change in the previous and subsequent months to identify the duration of the flow peak or trough; combined with high-frequency flow data, assessing whether the event has a significant lag effect or sudden fluctuation; finally, comparing with the years with similar intensity index in history, classifying and matching the characteristics of the current year's extreme event. The analysis results will form the persistence impact characteristic parameter items, including the duration (in days), the delay response time (in days), and the flow high variation interval, etc.

[0111] It should be noted that the identification of strong extreme hydrological events not only serves the runoff distribution analysis of abnormal years, but also provides important boundary conditions for subsequent dynamic correction of dry tributary contribution rates, and provides quantitative early warning basis for managers facing intra-year mutation risks. This process can be automatically executed by the model program without human intervention, and is easy to be coupled and integrated with the subsequent simulation process.

[0112] Further, step S5 comprises the following steps:

[0113] Step S51: Extracting multi-year historical runoff data of the basin where the target reservoir is located from the historical database, including the annual inflow sequence of the first tributary and the second tributary including concentration degree, concentration period and dry tributary contribution rate;

[0114] Step S52: Taking historical years as time variables, and taking concentration degree, concentration period and dry tributary contribution rate in annual inflow sequence as dependent variables, respectively, three sets of linear regression equations are established;

[0115] Step S53: Extracting the slope and intercept of the three sets of linear regression equations, taking the intercept of the regression equation as the hydrological benchmark value, and determining the change trend of the long-term inflow composition of the target reservoir through the slope of the regression equation;

[0116] Step S54: Adjusting the change trend of the long-term inflow composition of the target reservoir according to the persistence impact characteristics of the current year. When the persistence impact characteristics indicate a strong extreme event, multiply the slope of the change trend by the persistence strengthening coefficient to form the basin runoff simulation result of double tributary coupling, wherein the persistence strengthening coefficient is determined according to the intensity index of the extreme event, and the value range is 0.5-2.0.

[0117] In some embodiments, to achieve the long-term evolution trend prediction and coupling correction simulation of the target reservoir inflow composition, multi-year historical runoff data of the target reservoir basin is called from the control data center, and the data content includes the inflow sequence of the first tributary and the second tributary into the target reservoir, accompanied by the characteristic indicators generated by the foregoing, such as concentration, concentration period, and dry-tributary contribution rate in the corresponding year. To ensure the effectiveness of the regression modeling, the called data year limit is not less than 10 years, ensuring that the trend is reflected rather than periodicity or occasional disturbance.

[0118] The historical year is set as the independent variable (time variable), and the concentration, concentration period, and dry-tributary contribution rate are set as the dependent variables, respectively, to establish three linear regression models one by one. The scatter plot is drawn with the year as the horizontal axis and the concentration as the vertical axis, and the regression line of the change of the concentration with time is fitted. Then, the concentration period and the dry-tributary contribution rate are repeated in the above modeling process, and finally three regression equations with unified form are formed, the expression form is: Y=aX+b, where X is the year, a is the regression slope, b is the intercept, and Y represents the three dependent variables, respectively.

[0119] It should be noted that the linear regression model helps to identify whether there is a significant runoff reconstruction trend, such as continuous deviation of the dry-tributary ratio, advance of the concentration period, etc.

[0120] The slope and intercept of the above three regression equations are extracted, the intercept b is defined as the hydrological reference value of each indicator, which is the initial condition when the change trend does not exist, reflecting the state of the target reservoir before significant structural evolution occurs; and the positive and negative and absolute value of the slope a reflect the direction and strength of the long-term inflow structure evolution. For example, if the dry-tributary contribution rate regression line slope is negative, it means that the importance of the main stream is rising year by year, and the contribution of the tributary is gradually weakened. The concentration period slope is positive, which may imply the trend of early occurrence of flood, posing a pre-positioning risk to the regulation and dispatching strategy.

[0121] The completed extreme event recognition analysis result is called, the persistence influence characteristic and the corresponding extreme event intensity index of the current year are obtained, the index is mapped to a persistence reinforcement coefficient, the value range is controlled between 0.5 and 2.0, wherein the greater the index, the more extreme the event of the current year, and the more intense the response of the system to the trend influence. The specific mapping mode can adopt a segmented linear conversion function for normalization. For example, when the extreme event intensity index is 1.0, the corresponding persistence reinforcement coefficient is 1.0, and the slope is not changed; if the intensity index is 2.0, the persistence reinforcement coefficient is 2.0, and the slope is doubled, simulating the sensitive response of the system to the extreme situation. Finally, the regression slope is multiplied by the reinforcement coefficient to form a modified trend expression, and the current year inflow simulation value is coupled and adjusted. The operation automatically acts on the concentration, concentration period and dry-branch contribution rate in three directions, realizes the dynamic prediction and adaptive simulation of the future inflow trend of the target reservoir under the condition of double-branch flow coupling.

[0122] It should be noted that the regression modeling and trend adjustment process does not depend on manual intervention, and is automatically executed by the system. The data input port can access real-time updated remote sensing hydrological information or predicted meteorological variables, and support extrapolation prediction for future years. Therefore, this step not only has the function of historical trend analysis, but also has the simulation and adaptive ability to future change scenarios, which is a key link to realize the controlled hydrological regulation under the change of medium and long-term runoff structure.

[0123] The application also provides a hydrological coupling simulation system for executing the above-mentioned hydrological coupling simulation method, and the hydrological coupling simulation system comprises:

[0124] The flow recovery module is used for collecting long-term flow data of the first branch and the second branch into the target reservoir; obtaining the outflow and inflow data of the upstream controlled reservoir of the first branch and the second branch, and calculating the regulation and storage influence amount of the upstream controlled reservoir; and restoring the long-term flow data by using the regulation and storage influence amount to obtain an inflow sequence;

[0125] The runoff structure analysis module is used for calculating a runoff vector component of the inflow sequence to determine a concentration degree representing the runoff concentration degree of the first branch and the second branch and a concentration period representing the runoff concentration time; and quantifying a runoff intra-annual uneven distribution coefficient of the inflow sequence synchronously;

[0126] The dry-branch contribution rate module is used for determining a flood period and a dry period of the current year based on the concentration period; calculating a preliminary dry-branch contribution rate of each branch in the flood period and the dry period through the inflow sequence respectively, and correcting the preliminary dry-branch contribution rate by using the runoff intra-annual uneven distribution coefficient to obtain the dry-branch contribution rate;

[0127] An extreme event identification module is configured to take the concentration, the runoff intra-annual uneven distribution coefficient and the pre-calculated extreme value ratio as the judgment basis of the intensity of the extreme event, determine the strong extreme hydrological event and analyze the persistent impact characteristics;

[0128] A coupling trend simulation module is configured to take the concentration, the concentration period and the dry and branch contribution rate of the historical years as the independent variables, linearly analyze the change trend of the long-term inflow composition of the target reservoir, and adjust the simulation result of the basin runoff of the double-branch flow coupling according to the persistent impact characteristics of the current year.

[0129] Therefore, from any viewpoint, the embodiments should be considered as being exemplary and non-limiting, the scope of the application being defined by the appended claims and not by the above description, and all the changes falling within the meaning and the scope of the equivalent elements of the patent file are intended to be comprised in the present application.

[0130] The above description is merely that of a specific implementation of the present application, enabling a person skilled in the art to understand or implement the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application shall not be limited to these embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for coupled hydrological simulation, characterized in that, The method, applicable to a hydrological system comprising two tributaries flowing into a target reservoir, wherein the hydrological system includes a first tributary, a second tributary, and a target reservoir, includes the following steps: Step S1: Collect long-term flow data of the first and second tributaries entering the target reservoir; obtain the inflow and outflow data of the upstream control reservoirs of the first and second tributaries, and calculate the regulation and storage impact of the upstream control reservoirs; use the regulation and storage impact to restore the long-term flow data to obtain the inflow sequence. Step S2: Calculate the runoff vector components of the inflow sequence to determine the concentration degree, which characterizes the degree of runoff concentration in the first and second tributaries, and the concentration period, which characterizes the time of runoff concentration; simultaneously quantify the intra-annual runoff unevenness coefficient of the inflow sequence. Step S3: Determine the flood season and dry season of the year based on the concentration period; calculate the preliminary contribution rate of each tributary during the flood season and dry season using the inflow sequence, and adjust the preliminary contribution rate of each tributary using the annual runoff unevenness coefficient to obtain the contribution rate of each tributary. Step S3 is specifically as follows: Step S31: Taking the concentrated period as the center, the angle range extending 45 degrees forward and backward is determined as the flood period angle; Step S32: Convert the flood season angle into the corresponding monthly time period as the flood season of the year. When the angle range exceeds 0°-360°, use modulo 360° calculation to normalize the angle. Step S33: Determine the remaining months of the year, excluding the flood season, as the dry season; Step S34: Calculate the difference in flow between the first and second tributaries during the flood season and the sum of the total flow of the two tributaries during the flood season using the inflow sequence. Divide the difference in flow by the sum of the total flow of the two tributaries during the flood season to obtain the flow dominance ratio. Step S35: Calculate the flood season interaction factor by multiplying the flow advantage ratio by the pre-acquired sediment concentration ratio of the two tributaries. The flood season interaction factor indicates that if the flow of the first tributary is greater than that of the second tributary, the factor value is positive, and vice versa. The contribution rate of the high sediment concentration tributary is suppressed. Step S36: Calculate the ratio of the dry season flow of the second tributary to the dry season flow of the first tributary through the inflow sequence, and multiply the natural logarithm of the ratio by the exponential decay term to obtain the dry season interaction factor, where the exponential decay term is e raised to the power of negative k times the number of days of the dry season, and k is the geomorphic decay coefficient. Step S37: Divide the flood season flow of each tributary by the total flood season flow, and then multiply by (1 + flood season interaction factor). Divide the dry season flow of each tributary by the total dry season flow, and then multiply by (1 - absolute value of dry season interaction factor) to form the preliminary contribution rate of the main stream and tributaries. Step S38: Use the coefficient of uneven distribution of runoff within the year to adjust the weight of the preliminary contribution rate of the main stream and branch streams, and obtain the contribution rate of the main stream and branch streams. Step S4: Use concentration, runoff annual distribution unevenness coefficient and pre-calculated extreme value ratio as the basis for judging the intensity of extreme events, identify strong extreme hydrological events and analyze the characteristics of their lasting impact. Step S5: Statistically analyze the concentration degree, concentration period and contribution rate of the main stream and tributary in historical years. Using the concentration degree, concentration period and contribution rate of the main stream and tributary in historical years as independent variables, linearly analyze the changing trend of the long-term inflow composition of the target reservoir, and adjust the results of the watershed runoff simulation with dual tributary coupling according to the characteristics of the continuous impact of the current year.

2. The method for hydrological coupled simulation according to claim 1, characterized in that, Step S1 includes the following steps: Step S11: Install water level gauges, flow meters, and rain gauges at the inflow sections of the first and second tributaries of the target reservoir. Set up fixed monitoring piles at a distance of 1.5 times the river width from the inflow section, so that the water level gauges, flow meters, and rain gauges are perpendicular to the water flow direction. Step S12: Collect water level, flow velocity, and rainfall data at preset time intervals using a water level gauge, flow meter, and rain gauge, and transmit the data to the data center of the control reservoir via a 4G / GPRS network as long-term flow data; at the same time, obtain the inflow and outflow data of the upstream control reservoirs of the first and second tributaries; Step S13: Calculate the regulation and storage impact of the upstream controlling reservoir, where the regulation and storage impact = outflow - inflow + reservoir capacity change / calculation period length; use the regulation and storage impact to compensate for the impact of upstream controlling reservoir regulation and storage on long-term flow data to obtain the inflow sequence.

3. The method for hydrological coupled simulation according to claim 2, characterized in that, In step S2, the runoff vector components of the inflow sequence are calculated to determine the concentration degree, which characterizes the degree of runoff concentration in the first and second tributaries, and the concentration period, which characterizes the time of runoff concentration. Specifically: The inbound flow sequence is grouped and statistically analyzed by month. The average monthly flow value for each month is calculated, and a corresponding angular coordinate is assigned to each month. January corresponds to 0 degrees, and each month increases by 30 degrees. December corresponds to 330 degrees, which serves as the center angle of the month. Calculate the runoff vector components along the X and Y axes for each month's flow in the first and second tributaries, respectively. The formulas for calculating the component values ​​are as follows: In the formula, This is the sum of the vertical components of the runoff vector along the X-axis. For the first Average monthly traffic value Let the central angle of the i-th month be . This is the sum of the horizontal components of the runoff vector along the Y-axis. The concentration degree, which characterizes the degree of runoff concentration in the first and second tributaries, and the concentration period, which characterizes the time of runoff concentration, are determined by using runoff vector components.

4. The method for hydrological coupled simulation according to claim 3, characterized in that, The determination of the concentration degree, which characterizes the degree of runoff concentration in the first and second tributaries, and the concentration period, which characterizes the time of runoff concentration, using runoff vector components are specifically as follows: Calculate the composite lengths of the runoff vector components of the first and second tributaries, respectively, where the composite length is... ; The concentration degree, which characterizes the runoff concentration of the first and second tributaries, is calculated using the flow vector components, where the concentration degree = composite length / total runoff during the study period; When the sum of the horizontal components of the runoff vector on the Y-axis is greater than zero, the period of concentration is arctan( ); When the sum of the horizontal components of the runoff vector on the Y-axis is less than zero, the period of concentration is arctan( +180°; When the sum of the horizontal components of the runoff vector on the Y-axis is zero, and the sum of the vertical components of the runoff vector on the X-axis is greater than zero, the concentration period is 90°. When the sum of the horizontal components of the runoff vector on the Y-axis is equal to zero, and the sum of the vertical components of the runoff vector on the X-axis is less than zero, the concentration period is 270°.

5. The hydrological coupling simulation method according to claim 4, characterized in that, The formula for quantifying the intra-annual runoff unevenness coefficient of the inflow sequence in step S2 is as follows: In the formula, This is the coefficient for uneven distribution of runoff within the year, with a value ranging from 0 to 1.

0. For the number of months, This refers to the runoff volume for each month of the year. This represents the average monthly runoff volume within the year.

6. The method for hydrological coupled simulation according to claim 5, characterized in that, Step S38 includes: The maximum adjustment range of the initial contribution rate of the Heavenly Stems and Earthly Branches is denoted as the maximum correction range. The difference between the annual runoff distribution unevenness coefficient and the threshold of 0.7 is calculated and denoted as the unevenness difference. The non-uniformity difference is used as a correction intensity coefficient based on the mapped Sigmoid function; The contribution rate of the main stem and branch (or branch) is calculated using the initial contribution rate, maximum correction magnitude, and correction intensity coefficient, where the contribution rate of the main stem and branch during the flood season equals the initial contribution rate. (1 + maximum correction range) (Corrected intensity coefficient), the contribution rate of the stem and branch during the dry season = the initial contribution rate of the stem and branch. (1 - maximum correction range) (Corrected strength coefficient).

7. The hydrological coupling simulation method according to claim 6, characterized in that, Step S4 includes the following steps: Step S41: Calculate the ratio of the maximum monthly runoff to the minimum monthly runoff in the 12 months of the year using the inflow sequence, and use it as the ratio of monthly extreme values ​​within the year; Step S42: Calculate the ratio of the maximum annual runoff to the minimum annual runoff using the inflow sequence of historical years, and use it as the historical extreme value ratio; Step S43: Calculate the extreme event intensity index based on concentration, annual runoff unevenness coefficient, annual monthly extreme value ratio, and historical annual extreme value ratio to obtain the severe extreme hydrological event; the specific formula for calculating the extreme event intensity index is as follows: In the formula, For concentration, The coefficient for uneven distribution of runoff within the year. This represents the ratio of monthly extreme values ​​within the year. The ratio of historical extreme values ​​is given by K, which is a normalization constant. Step S44: Conduct a persistent impact analysis on severe extreme hydrological events to obtain persistent impact characteristics.

8. The method for hydrological coupled simulation according to claim 7, characterized in that, Step S5 includes the following steps: Step S51: Extract multi-year historical runoff data of the watershed where the target reservoir is located from the historical database, including the annual inflow sequence of the first and second tributaries, including concentration, concentration period and contribution rate of the main stream and tributaries; Step S52: Using historical years as the time variable, and using the concentration, concentration period, and contribution rate of the dry and tributary systems in the annual inflow sequence as dependent variables, establish three sets of linear regression equations; Step S53: Extract the slope and intercept of the three sets of linear regression equations, use the intercept of the regression equation as the hydrological baseline value, and determine the long-term trend of the inflow composition of the target reservoir by the slope of the regression equation. Step S54: Adjust the time scale of the long-term inflow composition of the target reservoir according to the persistent impact characteristics of the year. When the persistent impact characteristics indicate a strong extreme event, multiply the slope of the trend by the persistent enhancement coefficient to form the watershed runoff simulation results of dual-tributary coupling. The persistent enhancement coefficient is determined according to the extreme event intensity index and has a value range of 0.5-2.

0.

9. A system for coupled hydrological simulation, characterized in that, For executing the hydrological coupled simulation method as described in claim 1, the hydrological coupled simulation system comprises: The flow recovery module is used to collect long-term flow data of the first and second tributaries entering the target reservoir; obtain the inflow and outflow data of the upstream control reservoirs of the first and second tributaries, and calculate the regulation and storage impact of the upstream control reservoirs; and use the regulation and storage impact to restore the long-term flow data to obtain the inflow sequence. The runoff structure analysis module is used to calculate the runoff vector components of the inflow sequence to determine the concentration degree, which characterizes the degree of runoff concentration in the first and second tributaries, and the concentration period, which characterizes the time of runoff concentration; it also simultaneously quantifies the intra-annual runoff unevenness coefficient of the inflow sequence. The main stream and tributary contribution rate module is used to determine the flood season and dry season of the year based on the concentration period; the initial main stream and tributary contribution rate of each tributary during the flood season and dry season is calculated by using the inflow sequence, and the initial main stream and tributary contribution rate is weighted and corrected by the runoff annual distribution unevenness coefficient to obtain the main stream and tributary contribution rate. The extreme event identification module uses concentration, runoff annual distribution unevenness coefficient and pre-calculated extreme value ratio as the basis for judging the intensity of extreme events, identifying strong extreme hydrological events and analyzing their persistent impact characteristics. The coupling trend simulation module is used to statistically analyze the concentration, concentration period, and contribution rate of the main stream and tributary in historical years. It uses the concentration, concentration period, and contribution rate of the main stream and tributary in historical years as independent variables to linearly analyze the changing trend of the long-term inflow composition of the target reservoir. The simulation results of watershed runoff with dual tributary coupling are obtained by adjusting the simulation based on the characteristics of the continuous impact of the current year.

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