Method for synchronous determination of water yield characteristics of a watershed based on isotope mass balance

Abstract

The application discloses a kind of watershed water production characteristics synchronous determination method based on isotope mass balance, belong to watershed hydrological process monitoring technical field.Solve isotope hydrology segmentation due to the problem of low accuracy of water production characteristics determination caused by evaporation fractionation interference.This method determines the continuous determination of δ 18 D and δ O sequence of real-time series in single precipitation event, simultaneously using runoff automatic sampling unit to collect runoff sample and output correction runoff sequence;Runoff sample is determined δD, δ 18 O and dissolved Ar and Kr, and δ 18 O, deuterium surplus and C Ar / C Kr Restraint is introduced evaporation fractionation coefficient correction mass balance equation group, and is solved by Markov chain monte carlo method, and the uncertainty quantification result of event water production, water production coefficient and water source contribution rate is synchronously output.Mainly used in single precipitation event in event water and event water accurate segmentation and water production coefficient determination.

Description

Technical Field

[0001] This invention relates to the field of watershed hydrological process monitoring technology. More specifically, this invention relates to a method for simultaneous determination of watershed water yield characteristics based on isotope mass balance. Background Technology

[0002] Accurate determination of watershed water yield characteristics (such as the volume and runoff coefficient of runoff directly generated by a single precipitation event) is fundamental to hydrological forecasting, water resource management, and climate change impact assessment. However, the composition of river runoff is complex, including both surface runoff and shallow interflow directly generated by the current precipitation event (collectively referred to as event water), and pre-event water stored in the watershed soil and groundwater system before precipitation and displaced during the event. Accurately distinguishing the contributions of these two types of water sources within the total runoff has always been a core challenge in hydrological process research.

[0003] The binary mixing model based on stable isotopic mass balance is a classic method. Its basic principle is that if the water from the event has a significantly different isotopic composition from the pre-event water (e.g., δ¹⁸O⁻), then... 18 If the isotope concentration (O or δD) in the runoff is measured, the mixing ratio of the two can be calculated using the mass balance equation. However, this method faces significant challenges in its application to single precipitation events. For example, the paper "Flow pathways on steepforested hillslopes" published by McDonnell et al. in *Water Resources Research* shows that even in small watersheds with heavy rainfall events, pre-event water typically accounts for more than 50% of the total runoff, but this conclusion heavily relies on the assumption that the isotopic signal of the event water remains constant during runoff generation. In actual watersheds, after precipitation lands and before flowing into the river channel, it often undergoes significant surface evaporation, leading to preferential escape of light isotopes and non-equilibrium enrichment of heavy isotopes in the residual water. Therefore, the measured δD of the runoff may vary. 18 The O value has deviated from the original precipitation signal. If the model still uses the original precipitation isotope values ​​as the end-member of the event water in the calculation, it will incorrectly attribute the isotope changes caused by evaporation enrichment to the contribution of pre-event water, thus leading to a systematic overestimation of the proportion of pre-event water and a serious distortion of the water yield coefficient calculation results.

[0004] To overcome the interference of evaporation and fractionation, some studies have attempted to introduce deuterium surplus as a second isotopic parameter. Deuterium surplus is extremely sensitive to the evaporation process; the more intense the evaporation, the more significant the decrease in deuterium surplus value. However, even with the introduction of deuterium surplus, existing methods still face the fundamental limitation of difficult end-member calibration: the isotopic composition of water before the event is highly heterogeneous spatially, and the isotopic composition of the event water continues to change temporally with precipitation. Relying solely on two isotopic parameters (δ¹⁸O⁻ ... 18Simultaneously solving for the water ratio during the event (including O and deuterium surplus), the pre-event water ratio, and the degree of evaporation fractionation results in an inherently underdetermined equation system, where the uniqueness and reliability of the solution cannot be guaranteed. Therefore, there is an urgent need for a physical tracer that is unaffected by evaporation fractionation and can independently constrain the contribution of a specific endmember, thereby increasing model constraints and obtaining deterministic solutions.

[0005] Furthermore, another significant drawback of traditional methods lies in the acquisition of the input signal. Most existing technologies employ the deployment of one or more precipitation collectors within the watershed to collect cumulative mixed samples of single precipitation events for subsequent laboratory analysis. This approach is not only susceptible to errors introduced by sample evaporation and uneven mixing, but more importantly, it only provides an event-averaged value of the precipitation, completely missing information on the dynamic changes in precipitation isotopic composition during the precipitation process. When the actual precipitation's δ¹⁸O₁⁻¹... 18 When there are significant process variations in precipitation isotopes, using static average values ​​instead of dynamic input signals will directly lead to errors in the calibration of event water endmembers, resulting in high uncertainty in the final yield coefficient calculation. Therefore, how to obtain real-time dynamic sequences of precipitation isotopes and accurately calculate the weighted average input signal of event water based on them has become a crucial technical challenge that must be addressed to improve the accuracy of yield characteristic measurement.

[0006] In summary, the following shortcomings still exist in the accurate determination of watershed water yield characteristics: First, in the isotope mass balance model, there is a lack of physical tracers independent of the evaporation fractionation effect to constrain the contribution ratio of pre-event water, resulting in distorted water source segmentation results under evaporation interference; Second, traditional precipitation isotope sampling methods cannot obtain the real-time dynamic change process of precipitation isotopes, resulting in insufficient representativeness of the event water end-member input signal and large uncertainty in the model calculation results. Summary of the Invention

[0007] One object of the present invention is to solve at least the above-mentioned problems and to provide at least the advantages that will be described later.

[0008] Another objective of this invention is to provide a method for simultaneous determination of watershed water yield characteristics based on isotope mass balance, which involves simultaneously online determination of real-time precipitation isotope sequences and offline determination of runoff δ0.05. 18 The molar concentration ratios of O, deuterium surplus, and dissolved inert gases were used to construct a three-parameter coupled mass balance equation system. An evaporation fractionation coefficient was introduced for non-equilibrium enrichment correction, and the Markov chain Monte Carlo method was used to solve the equations together. This enabled the accurate and synchronous determination of event water production and production coefficient in a single precipitation event and the quantification of its uncertainty. This effectively solved the problem of measurement distortion caused by evaporation fractionation interference and insufficient representativeness of event water input signals in traditional methods.

[0009] To achieve these objectives and other advantages according to the present invention, a method for simultaneous determination of watershed water yield characteristics based on isotope mass balance is provided, comprising:

[0010] S1. In a single precipitation event, the δD and δ¹⁸ of the precipitation are continuously measured using an online precipitation sampler based on laser water isotope spectroscopy. 18 O Real-time sequence; Simultaneously, runoff process samples are collected synchronously using an automatic runoff sampling unit, and the runoff suspended solids concentration is measured online to output a runoff sequence corrected for suspended solids;

[0011] S2. Measure δD and δD of the runoff process sample. 18 The deuterium surplus was calculated, and the molar concentrations of dissolved inert gases Ar and Kr in the runoff sample were determined, and the molar concentration ratio R of Ar and Kr was calculated. r As a physical tracer to distinguish between pre-event water and event water;

[0012] S3. Construct a set of water-isotope-inert gas mass balance equations, using δ 18 The O and deuterium surplus dual isotope parameters constrain the water source mixing ratio, using R obtained in step S2. r The contribution ratio of water before the event is constrained, and the evaporation fractionation coefficient is introduced to correct the non-equilibrium enrichment of runoff isotopes;

[0013] S4. Using the Markov chain Monte Carlo method, the mass balance equations are solved jointly. Given the precipitation and the total runoff determined by the corrected runoff sequence, the event water production, water production coefficient and the relative contribution rate of pre-event water and event water are output simultaneously, and the posterior probability distribution and uncertainty interval of each result are given.

[0014] Among them, the δ of the water before the event in the mass balance equation set described in step S3 18 The values ​​for O and deuterium surplus are taken as the baseline isotopic values ​​of the river baseflow before the precipitation event, and the δ¹⁸O values ​​of the event water. 18 O is taken as the weighted average of the real-time precipitation sequence measured in step S1. The deuterium surplus of the event water is determined by δD and δD of the real-time precipitation sequence measured in step S1. 18 The result is calculated using O.

[0015] Preferably, the deuterium surplus is calculated using the following method: Deuterium surplus = δD - 8 × δ 18 O.

[0016] Preferably, the online precipitation sampler for laser water isotope spectroscopy analysis in step S1 employs cavity ring-down spectroscopy or off-axis integrating cavity output spectroscopy technology. After converting liquid precipitation into water vapor via a gas-liquid film permeation method, δD and δD are directly and continuously measured. 18O Real-time sequence; The automatic runoff sampling unit in step S1 has a built-in colorimetric cell. The online determination of runoff suspended matter concentration to output the runoff sequence after suspended matter correction is specifically as follows: the runoff suspended matter concentration is obtained online through the colorimetric cell, and the corrected runoff sequence is output after deducting its scattering interference.

[0017] Preferably, the molar concentration ratio R of dissolved inert gas Ar (argon) and Kr (krypton) in the runoff sample during step S2 is... r The measurements were performed using an indoor rare gas mass spectrometer.

[0018] Preferably, the δ of the water before the event described in step S3 is... 18 The baseline values ​​of O and deuterium surplus in the baseflow are determined by the automatic runoff sampling unit collecting river baseflow samples before a precipitation event, and δD and δ are measured according to the method described in step S2. 18 The result was obtained after calculation.

[0019] Preferably, the water-isotope-inert gas mass balance equation set in step S3 includes the following equations:

[0020] Water balance equation: Q = Q e +Q p ;

[0021] δ 18 O isotope mass balance equation: Q·δ 18 O r = Q e ·δ 18 O e +Q p ·δ 18 O p ;

[0022] Deuterium surplus mass balance equation: Q·d r =Q e ·d e +Q p ·d p ;

[0023] Mass balance equation for the molar concentration ratio of dissolved inert gases: Q·R r =Q e ·R e +Q p ·R p ;

[0024] Where Q is the total runoff obtained by integrating the corrected runoff sequence;

[0025] Q e For the aquatic water volume of the event;

[0026] Qp This refers to the water volume of aquatic products before the incident.

[0027] δ 18 O r δ for the runoff process sample measured in step S2 18 O value;

[0028] δ 18 O e For the event water δ 18 O value;

[0029] δ 18 O p δ of the water before the event 18 O value;

[0030] d r The deuterium surplus of the runoff process sample determined in step S2;

[0031] d e For the deuterium surplus of the event water;

[0032] d p The pre-event deuterium surplus in the water;

[0033] R r The molar ratio of Ar and Kr concentrations in the runoff sample determined in step S2;

[0034] R e The molar ratio of Ar and Kr concentrations in the event water;

[0035] R p The ratio of the molar concentrations of Ar and Kr in water before the event.

[0036] Preferably, the evaporation fractionation coefficient mentioned in step S3 is a correction parameter describing the non-equilibrium enrichment of isotopes caused by surface evaporation after precipitation lands and before it flows into the river channel. This coefficient is used as a variable to be solved in the mass balance equation set and is obtained by solving it together with other variables using the Markov chain Monte Carlo method.

[0037] Preferably, the step S3, which involves introducing an evaporation fractionation coefficient to correct the non-equilibrium enrichment of runoff isotopes, specifically involves: in the δ 18 In the O isotope mass balance equation and the deuterium surplus mass balance equation, the δ of the event water is considered. 18 O e and d e Replace each with the value corrected for the evaporation fractionation coefficient, and the corrected δ 18 O' e and d' e Substituting the δ 18 O eThe event water end-member positions in the isotopic mass balance equation and the deuterium surplus mass balance equation, replacing the original δ... 18 O e and d e :

[0038] δ 18 O' e =δ 18 O e +Δδ 18 O evap ;d' e =d e +Δd evap ;

[0039] Where, Δδ 18 O evap and Δd evap δ caused by evaporation and fractionation 18 The changes in O and deuterium surplus.

[0040] Preferably, when solving the Markov chain Monte Carlo method in step S4, the contribution ratio of pre-event water to event water is calculated for each runoff process sample point in the mass balance equation set, thereby obtaining the dynamic change sequence of the water source contribution ratio during the entire precipitation event.

[0041] The present invention has at least the following beneficial effects:

[0042] Firstly, this invention constructs a mass balance equation system coupled with water quantity, isotope, and inert gas, introducing the molar concentration ratio of dissolved inert gas as a physical tracer independent of evaporation and fractionation effects into the hydrological segmentation model, along with δ... 18 The O and deuterium surplus dual isotope parameters form a three-parameter joint constraint, which solves the problem that the equations are underdetermined and the pre-event water contribution is systematically overestimated due to non-equilibrium enrichment of evaporation in traditional two-component isotope models. It realizes the accurate synchronous measurement of event water production and water production coefficient in a single precipitation event and the quantification of its uncertainty.

[0043] Secondly, this invention employs a laser water isotope spectroscopy online precipitation sampler to continuously and in real-time measure the δD and δ of precipitation via a gas-liquid membrane permeation method. 18 The O-dynamic sequence, using the event weighted average as the input signal for the event water end-member, fully captures the process variation information of isotopic composition during a single precipitation event, solving the problems of insufficient end-member representativeness and large deviation in water yield coefficient calculation caused by the loss of process information in the traditional cumulative mixed sampling method.

[0044] Thirdly, this invention embeds the evaporation fractionation coefficient as a variable to be solved into δ. 18In the O and deuterium surplus mass balance equation, non-equilibrium enrichment correction is performed on the isotopic composition of the event water end element, which effectively eliminates the interference of isotopic fractionation caused by surface evaporation on the calculation of water source mixing ratio, restores the isotopic signal in the runoff that is distorted by evaporation, and improves the accuracy and reliability of the water production coefficient calculation results.

[0045] Fourth, this invention utilizes the Markov chain Monte Carlo method to solve the mass balance equations point by point, obtaining the dynamic change sequence and posterior probability distribution of the water source contribution ratio during the entire precipitation process, thus realizing a leap from a single static segmentation of water production characteristics to the quantitative analysis of uncertainty throughout the entire process.

[0046] Other advantages, objectives and features of the present invention will become apparent in part from the following description, and in part from those skilled in the art through study and practice of the invention. Detailed Implementation

[0047] The present invention will now be described in further detail with reference to specific technical solutions, so that those skilled in the art can implement it based on the description.

[0048] It should be understood that terms such as “having,” “comprising,” and “including” as used herein do not exclude the presence or addition of one or more other elements or combinations thereof.

[0049] This invention provides a method for simultaneous determination of watershed water yield characteristics based on isotope mass balance, comprising:

[0050] S1. In a single precipitation event, the δD and δ¹⁸ of the precipitation are continuously measured using an online precipitation sampler based on laser water isotope spectroscopy. 18 O Real-time sequence; Simultaneously, runoff process samples are collected synchronously using an automatic runoff sampling unit, and the runoff suspended solids concentration is measured online to output a runoff sequence corrected for suspended solids;

[0051] S2. Measure δD and δD of the runoff process sample. 18 The deuterium surplus was calculated, and the molar concentrations of dissolved inert gases Ar and Kr in the runoff sample were determined, and the molar concentration ratio R of Ar and Kr was calculated. r As a physical tracer to distinguish between pre-event water and event water;

[0052] S3. Construct a set of water-isotope-inert gas mass balance equations, using δ 18 The O and deuterium surplus dual isotope parameters constrain the water source mixing ratio, using R obtained in step S2. r The contribution ratio of water before the event is constrained, and the evaporation fractionation coefficient is introduced to correct the non-equilibrium enrichment of runoff isotopes;

[0053] S4. Using the Markov chain Monte Carlo method, the mass balance equations are solved jointly. Given the precipitation and the total runoff determined by the corrected runoff sequence, the event water production, water production coefficient and the relative contribution rate of pre-event water and event water are output simultaneously, and the posterior probability distribution and uncertainty interval of each result are given.

[0054] Among them, the δ of the water before the event in the mass balance equation set described in step S3 18 The values ​​for O and deuterium surplus are taken as the baseline isotopic values ​​of the river baseflow before the precipitation event, and the δ¹⁸O values ​​of the event water. 18 O is taken as the weighted average of the real-time precipitation sequence measured in step S1. The deuterium surplus of the event water is determined by δD and δD of the real-time precipitation sequence measured in step S1. 18 The result is calculated using O.

[0055] In the above technical solution, δD represents the abundance ratio of deuterium (D) to hydrogen (H) in the sample, which is a fraction of a thousandth relative to the deuterium-to-hydrogen ratio in the standard substance; δ 18 O represents the abundance ratio of oxygen-18 to oxygen-16 in the sample, a percentage of one thousandth relative to the standard.

[0056] In the above technical solution, the start and end times of a single precipitation event in step S1 are determined jointly by the water level trigger signal of the precipitation sampler and a preset no-precipitation time threshold. The trigger threshold for the water level trigger signal is defined as the start of a precipitation event when the water level rise rate in the rainwater collection funnel of the precipitation sampler is ≥0.1 mm / min for more than 3 minutes. The no-precipitation time threshold is 120 minutes, meaning that the current precipitation event ends when the precipitation sampler has not detected any effective precipitation for 120 consecutive minutes (no rise in water level in the rainwater collection funnel or cumulative increase <0.1 mm). If the interval between two precipitation events is less than 120 minutes, they are merged into a single precipitation event. The above thresholds can be calibrated before implementation based on the watershed climate characteristics: a 90-minute threshold can be used in humid regions, and a 180-minute threshold can be used in arid regions. The collection of runoff process samples in step S1 and the output of the corrected runoff sequence are synchronously corresponding in time, so that each runoff sample can correspond to a specific time point in the runoff sequence. The online measurement and correction of runoff suspended solids concentration by the automatic runoff sampling unit in step S1 is achieved in the following way: The absorbance of the runoff is measured at multiple wavelengths using a built-in colorimetric cell. An initial concentration value is obtained by establishing a standard curve of suspended solids concentration versus absorbance. Simultaneously, the scattering interference at short wavelengths is subtracted using the absorbance signal at longer wavelengths, and the corrected suspended solids concentration value is output. The runoff flow signal is then compensated in real time based on this corrected concentration. The scattering interference subtraction uses a dual-wavelength correction method: the absorbance A2 at a near-infrared wavelength λ2 = 810 nm is selected as the scattering reference (at this wavelength, scattering by suspended solids is the main contributor, and absorption by dissolved substances is negligible); the absorbance A1 at a visible light wavelength λ1 = 520 nm is selected as the suspended solids concentration measurement wavelength. The corrected suspended solids concentration C... ss =(A1-α·A2) / (β·L), where α is the empirical coefficient of the scattering intensity ratio between wavelengths λ1 and λ2, taken as α = 1.2~1.8, calibrated based on the particle size distribution characteristics of suspended matter in the watershed; β is the slope of the standard curve between suspended matter concentration and absorbance (obtained through multi-concentration gradient calibration using suspended matter samples collected on-site in the watershed, unit L / mg·m); and L is the optical path length of the cuvette (m). The corrected runoff volume Q corr =Q raw / (1-η·C ss ), where Q raw η represents the original output flow rate of the flow meter, and η is the conversion factor between the suspended solids volume concentration and the flow rate attenuation coefficient, which is obtained through laboratory calibration.

[0057] In the above technical solution, the δD and δ of the runoff process sample in step S2 18O, offline determination was performed using an indoor liquid water isotope analyzer or isotope mass spectrometer. The molar ratio R of Ar and Kr in the event water described in step S3 was... e The value is taken as the theoretically calculated ratio under equilibrium conditions of precipitation and atmospheric dissolution, derived from Henry's Law C. i =H i (T)×P i The Henry's constants for Ar and Kr were calculated using data published by Weiss (1970) and Weiss & Kyser (1978). Atmospheric partial pressures were calculated using the atmospheric pressure values ​​observed synchronously at the basin meteorological stations during precipitation and the volume fractions of Ar (0.934%) and Kr (1.14 ppm) in the atmosphere. Temperature T was taken as the arithmetic mean of the measured atmospheric temperatures during precipitation. According to Henry's law, the solubility of a gas in a liquid phase is related to its partial pressure and temperature. The Henry's constants of different inert gases show significant differences in their response rates to temperature changes: the enthalpy change of Kr is greater than that of Ar, therefore, the solubility of Kr is more sensitive to temperature changes than that of Ar. Therefore, the Ar / Kr molar concentration ratio in water is essentially a sensitive function of the water body's temperature history, and water bodies formed under different temperature conditions have different characteristic R values. For a single precipitation event, the temperature of the event water (i.e., the runoff directly generated by the precipitation) during the initial stages of precipitation and infiltration is the near-surface air temperature at the time of the precipitation event, representing a short-duration instantaneous temperature signal. In contrast, the temperature of the pre-event water (i.e., baseflow or groundwater) stored within the watershed is controlled by the multi-year average air temperature of the watershed or the average ground temperature of the recharge area, representing a long-term stable temperature signal. Because the instantaneous air temperature of a single precipitation event usually differs systematically from the annual average air temperature of the watershed (especially in areas with distinct seasonal climate characteristics), the Ar / Kr molar concentration ratio dissolved in the event water and the pre-event water shows a measurable and statistically significant difference. This ratio difference does not involve isotopic fractionation processes and is unaffected by surface evaporation, thus providing a δ-dependent equation for the mass balance system. 18 Orthogonal physical constraints for O and deuterium surplus.

[0058] The molar ratio R of Ar and Kr in the water before the event described in step S3 p The values ​​are multiple C values ​​obtained from the actual measurement of the base current sample. Ar / C Kr The arithmetic mean or median, and the coefficient of variation (CV = standard deviation / mean) of multiple Ar and Kr molar concentration ratios of the baseflow sample before the precipitation event are less than 5%, R p The value is usually considered a constant in the hydrological segmentation process of a single precipitation event. If the baseflow sample R... p For a coefficient of variation ≥5%, multiple baseflow samples should be collected at different time points before the precipitation event (at least 3 time points, covering different flow conditions within 24 hours before the event) to determine R. pTake their arithmetic mean as R p Input values, and R will be used in subsequent Markov chain Monte Carlo solutions. p The uncertainty (expressed as the standard deviation of the measured values) is incorporated into the prior distribution for propagation, and the uncertainty interval of the final output water source contribution rate includes R. p The contribution of variability.

[0059] In the above technical solution, the precipitation in step S4 is obtained by synchronous observation from independently deployed rain gauges and represents the cumulative precipitation of a single precipitation event. The event water yield in step S4 is the portion of the total runoff directly generated by the current precipitation event, and the water yield coefficient is the ratio of the event water yield to the precipitation. The final output of the method includes: the event water yield value and its posterior probability distribution for a single precipitation event, the water yield coefficient value and its posterior probability distribution, and the change in the relative contribution rate of pre-event water and event water over time. The posterior probability distribution and uncertainty interval in step S4 include the 95% confidence intervals for the event water yield and water yield coefficient, determined by the 2.5 percentile and 97.5 percentile of the posterior probability distribution of the corresponding variables.

[0060] The above technical solution organically integrates laser water isotope spectroscopy online analysis technology with inert gas tracing technology, enabling the simultaneous acquisition of real-time precipitation isotope sequences, runoff isotope composition, and C2O2 content during a single precipitation event. Ar / C Kr Independent tracer data were used to construct a three-parameter coupled mass balance equation set of water quantity, isotope and inert gas, which changed the limitation of traditional hydrological segmentation methods that only rely on single or dual isotope constraints. This enabled the accurate separation of the contribution of pre-event water and event water under the interference of evaporation and distillation, and realized the synchronous, quantitative and uncertainty-assessable determination of watershed water yield characteristics.

[0061] In one of the technical solutions, the deuterium surplus is calculated using the following method: Deuterium surplus = δD - 8 × δ 18 O provides a standardized computational basis for embedding the deuterium surplus as a constraint parameter independent of a single isotope into the mass balance equations, avoiding inconsistencies in water source segmentation results due to differences in definition.

[0062] In one technical solution, the online precipitation sampler for laser water isotope spectroscopy analysis in step S1 employs cavity ring-down spectroscopy or off-axis integrating cavity output spectroscopy technology. After converting liquid precipitation into water vapor via a gas-liquid film permeation method, δD and δD are directly and continuously measured. 18The real-time sequence is as follows: In step S1, the automatic runoff sampling unit has a built-in colorimetric cell. The online measurement of runoff suspended solids concentration to output a runoff sequence corrected for suspended solids specifically involves: acquiring the runoff suspended solids concentration online through the colorimetric cell, and outputting the corrected runoff sequence after deducting its scattering interference. By limiting the precipitation sampler to use cavity ring-down spectroscopy or off-axis integrating cavity output spectroscopy, and directly measuring the liquid precipitation after converting it into water vapor through gas-liquid film permeation, the continuity and high accuracy of the real-time precipitation isotope sequence are ensured. At the same time, limiting the runoff sampling unit to have a built-in colorimetric cell and outputting the corrected runoff sequence after deducting scattering interference effectively eliminates the interference of high suspended solids concentration during the precipitation period on the flow monitoring signal, providing a more accurate total runoff data basis for subsequent water balance calculations.

[0063] In one technical solution, the molar concentration ratio Rr of dissolved inert gases Ar and Kr in the runoff sample during step S2 is determined using an indoor rare gas mass spectrometer. This fully utilizes the high sensitivity of rare gas mass spectrometry for trace inert gases, ensuring the accuracy of C... Ar / C Kr The measurement accuracy of this key physical tracer parameter provides reliable data support for establishing the constraint equation for the molar concentration ratio of dissolved inert gases in the mass balance equation set.

[0064] In one of the technical solutions, the δ of the water before the event mentioned in step S3 18 The baseline values ​​of O and deuterium surplus in the baseflow are determined by the automatic runoff sampling unit collecting river baseflow samples before a precipitation event, and δD and δ are measured according to the method described in step S2. 18 The baseline values ​​of the river baseflow isotopes before the precipitation event, as described in step S3, are determined as follows: Within 24 hours before the precipitation event, and under the condition that the river flow is stable and there is no rainfall interference, the automatic runoff sampling unit continuously collects at least three river baseflow samples at the watershed outlet section at equal time intervals of not less than 6 hours. The δD and δδ values ​​of each sample are then measured according to the method described in step S2. 18 The O value was calculated and the deuterium surplus was determined. The arithmetic mean of the measurement results of each sample was taken as the baseline isotopic value of the pre-event water. It should be noted that although the isotopic composition of pre-event water at different spatial locations within the watershed objectively exhibits some heterogeneity, the baseflow samples collected at the watershed outlet section are essentially a comprehensive signal after flow-weighted mixing of upstream spatial water sources at the confluence outlet. This mixed signal represents the average end-member composition of pre-event water at the watershed outlet section, and therefore possesses the validity as a single pre-event water end-member in a two-component mixing model. If the δ¹⁴ ... 18If the coefficient of variation (CV = standard deviation / mean) of the measured values ​​of O or deuterium surplus exceeds 5%, it indicates that there is a non-negligible spatiotemporal variability in the water end-members before the event. In this case, in the Markov chain Monte Carlo solution in step S4, instead of simply using a single arithmetic mean, the standard deviation of each sample measurement is used as the prior distribution input of the end-member uncertainty. This ensures that the uncertainty interval of the final output water source contribution rate simultaneously includes the component caused by the spatial heterogeneity of the water end-members before the event, thereby ensuring the objectivity of the water source segmentation results and the completeness of uncertainty quantification. The baseline values ​​of water isotopes before the event are directly collected from river baseflow samples by the runoff sampling unit before the precipitation event and measured according to the same analysis procedure as the runoff samples. This ensures the consistency of the water end-member values ​​and the runoff sample measurements in terms of analysis methods and systematic errors, eliminates the systematic bias introduced by different end-member calibration methods, and improves the internal consistency of the water source segmentation results.

[0065] In one of the technical solutions, the water-isotope-inert gas mass balance equations in step S3 include the following equations:

[0066] Water balance equation: Q = Q e +Q p ;

[0067] δ 18 O isotope mass balance equation: Q·δ 18 O r = Q e ·δ 18 O e +Q p ·δ 18 O p ;

[0068] Deuterium surplus mass balance equation: Q·d r =Q e ·d e +Q p ·d p ;

[0069] Mass balance equation for the molar concentration ratio of dissolved inert gases: Q·R r =Q e ·R e +Q p ·R p ;

[0070] Where Q is the total runoff obtained by integrating the corrected runoff sequence;

[0071] Q e For the aquatic water volume of the event;

[0072] Q p This refers to the water volume of aquatic products before the incident.

[0073] δ 18 O r δ for the runoff process sample measured in step S2 18 O value;

[0074] δ 18 O e For the event water δ 18 O value;

[0075] δ 18 O p δ of the water before the event 18 O value;

[0076] d r The deuterium surplus of the runoff process sample determined in step S2;

[0077] d e For the deuterium surplus of the event water;

[0078] d p The pre-event deuterium surplus in the water;

[0079] R r The molar ratio of Ar and Kr concentrations in the runoff sample determined in step S2;

[0080] R e The molar ratio of Ar and Kr concentrations in the event water;

[0081] R p The ratio of the molar concentrations of Ar and Kr in water before the event.

[0082] In the above technical solution, the molar concentration ratio R of Ar and Kr in the event water is... e The value is the theoretical dissolution ratio at precipitation-atmosphere equilibrium, or it can be obtained from actual measurements of precipitation samples, which are continuously collected by the precipitation sampler; the ratio of Ar and Kr molar concentrations R of water before the event. p The value is taken as a ratio constant obtained from the measured baseline sample. When solving the mass balance equations using the Markov chain Monte Carlo method, the variables to be solved include Q. e With Q p The value of , and the evaporation fractionation coefficient.

[0083] The above technical solution concretizes the mass balance equations into water quantity, δ 18 The four independent equations—O, deuterium surplus, and the molar concentration ratio of dissolved inert gases—give the mathematical model with three-parameter coupled constraints a clear structure and a well-defined solution objective. Among them, the equation for the molar concentration ratio of dissolved inert gases, as a physical constraint equation independent of isotope fractionation, provides a crucial additional constraint for solving the water source segmentation problem under evaporation interference.

[0084] In one of the technical solutions, the evaporation fractionation coefficient mentioned in step S3 is a correction parameter describing the non-equilibrium enrichment of isotopes caused by surface evaporation after precipitation lands and before it flows into the river channel. The evaporation fractionation coefficient is used as a variable to be solved in the mass balance equation set and is obtained by solving it together with other variables using the Markov chain Monte Carlo method.

[0085] In the above technical solution, the evaporation fractionation coefficient ε and Δδ mentioned in step S3 18 O evap , Δd evap The quantitative relationship between them is: Δδ 18 O evap =-ε·ln(f); Δd evap =-k·ε·ln(f); where ε is the evaporation fractionation coefficient; f is the proportion of residual water in the water body before it flows into the river channel after precipitation lands, obtained when solving the mass balance equations; k is the response coefficient of deuterium surplus to evaporation fractionation, generally taken as 0.4~0.6, the drier the evaporation environment, the smaller the value of k; in humid areas or watersheds with good vegetation cover, k is taken as 0.5~0.6; in arid and semi-arid areas or watersheds with bare land, k is taken as 0.4~0.5. Generally, when evaporating from open water bodies or humid surfaces, k is taken as 0.5. The evaporation fractionation system is defined as a correction parameter describing the non-equilibrium enrichment of isotopes after precipitation lands and before it flows into the river channel, and it is used as a variable to be solved in the mass balance equations rather than a preset fixed value, so that the model can dynamically determine the fractionation degree according to the actual evaporation conditions of each precipitation event, avoiding the problem of insufficient applicability of fixed evaporation correction parameters under different meteorological and vertical conditions.

[0086] In one technical solution, step S3, which involves introducing an evaporation fractionation coefficient to correct the non-equilibrium enrichment of runoff isotopes, specifically involves: in the δ 18 In the O isotope mass balance equation and the deuterium surplus mass balance equation, the δ of the event water is considered. 18 O e and d e Replace each with the value corrected for the evaporation fractionation coefficient, and the corrected δ 18 O' e and d' e Substituting the δ 18 O e The event water end-member positions in the isotopic mass balance equation and the deuterium surplus mass balance equation, replacing the original δ... 18 O e and d e :

[0087] δ 18 O' e =δ 18 Oe +Δδ 18 O evap ;d' e =d e +Δd evap ;

[0088] Where, Δδ 18 O evap and Δd evap δ caused by evaporation and fractionation 18 The changes in O and deuterium surplus.

[0089] The above technical solution specifies the evaporation fractionation correction as being applied to δ 18 The O and deuterium surplus balance equations incrementally correct the event water end element value, clarifying the position and form of the correction mathematical operation. This allows the non-equilibrium enrichment effect caused by evaporation to be quantitatively characterized rather than qualitatively described in the model, ensuring that the corrected mass balance equation can truly reflect the superposition process of water source mixing and evaporation fractionation.

[0090] In one of the technical solutions, when solving the Markov chain Monte Carlo method in step S4, the contribution ratio of pre-event water to event water is calculated for each runoff process sample point in the mass balance equation set, thereby obtaining the dynamic change sequence of the water source contribution ratio during the entire precipitation event.

[0091] In the above technical solution, when using the Markov chain Monte Carlo method for joint solution in step S4, the variables to be solved include the event water production volume Q. e Pre-event aquatic water volume Q p The proportion of residual water f and the evaporation fractionation coefficient ε, where Q e With Q p The constraints of the water balance equation are satisfied. The Markov chain Monte Carlo method is used to solve the problem, employing a Bayesian inference framework, with the measured δ values ​​of samples from each runoff process as the basis. 18 O, d r and R r Using the observed data and the aforementioned mass balance equations as a forward model, after setting prior distributions for each variable to be solved, the posterior probability distributions of each variable are obtained through iterative sampling. The Markov chain Monte Carlo method employs the No-U-Turn Sampler (NUTS) algorithm for posterior sampling, setting up four parallel Markov chains. Each chain has a warm-up period of 2000 iterations and a formal sampling period of 4000 iterations, with a total effective sample size of no less than 8000. The prior distributions for each variable to be solved are set as follows: Event Aquatic Productivity Q e The aquatic water volume follows a uniform distribution U(0,Q), and the water volume before the event is Q. p From the water balance equation Q=QQ eIt is confirmed that the evaporation fractionation coefficient ε follows a uniform distribution U(0,0.05) (corresponding to δ). 18 The maximum enrichment level of O is approximately 50‰; the proportion of residual water f follows a uniform distribution U(0.1,1). The convergence criterion is a Gelman-Rubin reduction factor <1.05 and an effective sample size (neff) greater than 1000. The 2.5 percentile and 97.5 percentile of the posterior distribution are used as the upper and lower limits of the 95% confidence interval, respectively.

[0092] In the above technical solution, the relative contribution rate of pre-event water and event water in step S4 is expressed as Q for each runoff process sample point. p / Q and Q e The value is expressed as a percentage of / Q, where Q is the total runoff determined by the corrected runoff sequence at the corresponding time point of the sample point. By solving the mass balance equations for each runoff sample point, the traditional method, which can only output single-average results, is extended to obtain a dynamic sequence of the proportion of water source contribution throughout the entire precipitation process. This elevates the analysis of runoff characteristics from static endmember segmentation to process analysis, providing high-temporal-resolution quantitative information for revealing the evolution of runoff generation mechanisms at different stages of precipitation.

[0093] It is worth noting that in the equation system constructed in this invention, the evaporation fractionation coefficient ε and the residual water ratio f appear mathematically in a product-coupled form. To improve the identifiability of the parameters, this application adopts one of two strategies for constraint: (1) Based on the basin meteorological observation data (2-meter wind speed, relative humidity, and air temperature), the value of ε is pre-calculated independently using the improved Penman formula, and it is used as a known quantity input into the mass balance equation system. At this time, ff can be uniquely solved by the isotope equation; or (2) ff is parameterized as a monotonic function of runoff recession time, and global nonlinear regression is performed using multiple sample points of the entire flood event, thereby realizing the joint identification of ε and f. The above strategies ensure the mathematical closure of the model and the uniqueness of the solution.

[0094] The following uses a rainfall event as an example to illustrate the method described in this application in detail.

[0095] 1. Simultaneous sampling of precipitation and runoff

[0096] At 14:23 on June 12, 2025, the water level in the rainwater collection funnel of the precipitation sampler rose at a rate of 0.15 mm / min for more than 3 minutes, triggering the precipitation event initiation signal. From the trigger moment, the online precipitation sampler (model: LGR LWIA-45-EP) using laser water isotope spectroscopy with cavity ring-down spectroscopy technology directly and continuously measured the δD and δδ values ​​of the precipitation after converting liquid precipitation into water vapor via a gas-liquid film permeation method. 18The real-time sequence was measured once per minute. By 08:47 on June 13th, the precipitation sampler had detected no effective precipitation for 120 consecutive minutes (cumulative increase <0.1 mm), thus the precipitation event was deemed over. The event lasted approximately 18.4 hours, and the cumulative precipitation, synchronously measured by an independently deployed tipping bucket rain gauge, was 46.8 mm.

[0097] Simultaneously, an automatic runoff sampling unit (with a built-in colorimetric cell and an optical path length of L=0.01 m) was deployed at the watershed outlet section. Runoff samples were automatically collected at 30-minute intervals starting from the precipitation trigger signal, totaling 37 samples. The colorimetric cell simultaneously measured the absorbance A1 and A2 at wavelengths λ1=520 nm and λ2=810 nm, and output the runoff volume sequence after scattering correction and suspended matter correction. The corrected runoff volume Q... corr =Q raw / (1-η·C ss ), where η was laboratory-calibrated to be 0.032 L / g, C ss =(A1-α·A2) / (β·L), where α is taken as 1.5 (calibrated based on the suspended matter particle size distribution characteristics of the watershed), and β is calibrated to 2.87 L / (mg·m) using multiple concentration gradients of suspended matter samples from the watershed. Integrating the corrected runoff series over time yields the total runoff of this rainfall event, Q = 12.74 × 10⁻⁶. 4 m 3 .

[0098] 2. Indoor analysis of runoff samples and determination of end-member parameters

[0099] For the 37 runoff process samples collected, δD and δ¹⁸O were determined using an indoor liquid water isotope analyzer (model: Picaro L2130-i). 18 O value, and according to the deuterium surplus = δD - 8 × δ 18 The deuterium surplus of each sample was calculated. Simultaneously, the molar concentrations of dissolved inert gases Ar and Kr in each runoff sample were determined using an indoor rare gas mass spectrometer (Thermo Scientific Helix SFT), and the molar concentration ratio R was calculated. r= C Ar / C Kr The results of the measurements of some representative samples are shown in Table 1.

[0100] Table 1 Representative Measurement Results of Runoff Process Samples

[0101] Sampling time <![CDATA[Q corr (m 3 / s)]]> <![CDATA[δ 18 THE r (‰)]]> <![CDATA[d r (‰)]]> <![CDATA[R r (%)]]> 6-12 15:00 0.62 -7.05 10.4 39.6 6-12 17:30 2.15 -8.12 8.0 39.9 6-12 20:00 4.87 -8.82 5.6 40.1 6-12 22:30 3.96 -8.45 7.2 40.0 6-13 01:00 2.58 -8.03 8.5 39.8 6-13 04:00 1.43 -7.52 9.6 39.7 6-13 07:00 0.78 -7.10 10.2 39.6

[0102] Within 24 hours prior to the precipitation event, three baseflow samples were collected at the watershed outlet section using an automatic runoff sampling unit (collected at 08:00, 14:00, and 20:00, respectively). δD and δ were measured using the same method described above. 18 O and calculate the deuterium surplus, δ for 3 samples 18 The oxygen concentrations were -6.23‰, -6.18‰, and -6.31‰, respectively, and the deuterium surpluses were 11.2‰, 11.6‰, and 10.9‰, respectively. The arithmetic mean was taken as the baseline isotopic value of water before the event: δ 18 O p =-6.24‰, dp=11.2‰. R of the three base current samples p The measured values ​​were 39.5, 39.8, and 39.2, with a mean of 39.5 (CV = 0.76% < 5%). The arithmetic mean was taken as the R-value of the water before the event. p Enter the value.

[0103] δ of the event water 18 O e The value is taken as the weighted average of the measured real-time precipitation series. The precipitation δ in this precipitation event was calculated. 18 The weighted average precipitation value for O is -9.87‰, and the precipitation deuterium surplus (derived from real-time δD and δ 18 The weighted average of precipitation (calculated using O) is 6.5‰. The R of the event water... e Calculated using Henry's Law: Based on the air pressure (average 98.7 kPa) and air temperature (average 24.5℃) synchronously observed at the basin meteorological stations during the precipitation period, using Weiss's (1970) Henry's constant Ar and Weiss & Kyser's (1978) Henry's constant Kr, combined with the volume fractions of Ar (0.934%) and Kr (1.14 ppm) in the atmosphere, R is calculated. e =40.2.

[0104] 3. Construction and MCMC solution of the mass balance equations, with k set to 0.5. The Markov chain Monte Carlo method (No-U-Turn Sampler algorithm) is used to solve the above equations point-by-point. Four parallel Markov chains are set up, each chain having 2000 iterations in the pre-burn-in period and 4000 iterations in the formal sampling. The prior distribution of each variable to be solved is set as follows: Q e U(0,Q), εU(0,0.05), fU(0.1,1). Convergence criterion: Gelman-Rubin reduction factor < 1.05. Taking the sample point at 17:30 in Table 1 as an example, the solution is: Q e =2380 m 3 (Approximately 61.5%), Q p ==1490m 3 The corrected event water element δ18 O' e =-8.91‰ (significantly heavier than the original precipitation of -9.87‰, reflecting the enrichment effect of surface evaporation), d' e =5.1‰ (lower than the original precipitation of 6.5‰, reflecting the effect of evaporation on reducing the deuterium surplus). The posterior mean values ​​of ε and f for this sample point are 0.032 and 0.68, respectively.

[0105] 4. For each of the 37 runoff process sample points, the dynamic change sequence of the contribution ratio of event water to pre-event water during the entire rainfall process was obtained. The Q values ​​at each time point were then calculated. e Integrating over the entire event, we obtain the event-specific water yield Q of the precipitation event. e,total =7.62×10 4 m 3 Water production coefficient = Q e,total Rainfall = 7.62 × 10 4 m 3 / (46.8×10 -3 ×32.5×10 6 ) = 7.62 × 10 4 / 1.521×10 6 ≈0.0501. The 95% confidence interval for the posterior probability distribution of each parameter is: Event Aquatic Production 7.62 × 10 4 m 3 [7.35×10 4 7.89×10 4 ], water production coefficient 0.0501 [0.0483, 0.0519].

[0106] To verify the accuracy of the method of this invention, the following two independent methods were used for comparative verification:

[0107] (1) Comparison with the traditional isotope binary model: If the evaporation fractionation correction is ignored (i.e., ε and f are not introduced, and the original precipitation δ is directly used), 18 O e =-9.87‰ and d e Using 6.5‰ as the event water terminus, and employing a traditional two-component isotope model to solve for the same set of runoff samples, the event water yield was found to be 6.03 × 10⁻⁶. 4 m 3 The water production coefficient was 0.0396, which is about 21% lower than the result of this invention. Taking the sample point near the flood peak (20:00, δ...) as an example... 18 O r =-8.821‰, d rTaking an event water contribution rate of 5.5‰ as an example, the contribution rate of the event water calculated by this invention is 78.5%, while the traditional method (without evaporation correction) only yields 61.2%, a difference of 17.3%. This invention corrects the event water endmember to δ by introducing evaporation fractionation correction. 18 O' e =-8.91‰ (weight change) enables the model to correctly identify the isotope enrichment effect caused by evaporation, avoiding the systematic underestimation of the event's aquatic production by traditional methods.

[0108] (2) Comparison with the watershed water balance method: Based on the measured flow process curve at the watershed outlet section, the baseflow (i.e., pre-event water) and direct runoff (i.e., event water) were independently separated using the digital filtering method (Eckhardt recursive digital filtering method, with a filtering parameter of 0.98). The direct runoff of this rainfall event was found to be 7.48 × 10⁻⁶. 4 m 3 The water production coefficient is 0.0492. The results of this invention (7.62 × 10⁻⁶) 4 m 3 The relative deviation between the results obtained by the method (0.0501) and the results obtained by the water balance method was only 1.9%, which completely overlapped within the 95% confidence interval, verifying the accuracy and reliability of the measurement results of this invention.

[0109] Furthermore, the dynamic changes in the proportion of event-driven water contribution throughout the rainfall process are consistent with the theoretical expectations of the watershed runoff generation mechanism: in the early stage of rising water (15:00-17:30), the proportion of event-driven water gradually increases from about 38% to about 61%; in the later stage of rising water to the peak period (17:30-20:00), the proportion of event-driven water rapidly increases to 78%-85%, becoming the dominant component of runoff; in the receding stage (after 22:30), the proportion of event-driven water gradually decreases to about 45%-52%. This dynamic change process is highly consistent with the physical understanding that the watershed's runoff generation mechanism is dominated by groundwater recharge in the early stage and by direct runoff during the peak period, further verifying the reliability of the method of this invention in obtaining the dynamic change sequence of the water source contribution proportion from a process perspective.

[0110] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. They can be applied to various fields suitable for the present invention. For those skilled in the art, other modifications can be easily made. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details and the specific technical solutions shown and described herein.

Claims

1. A method for simultaneous determination of watershed water yield characteristics based on isotope mass balance, characterized in that, include: S1. In a single precipitation event, the δD and δ¹⁸ of the precipitation are continuously measured using an online precipitation sampler based on laser water isotope spectroscopy. 18 O Real-time sequence; Simultaneously, runoff process samples are collected synchronously using an automatic runoff sampling unit, and the runoff suspended solids concentration is measured online to output a runoff sequence corrected for suspended solids; S2. Measure δD and δD of the runoff process sample. 18 The deuterium surplus was calculated, and the molar concentrations of dissolved inert gases Ar and Kr in the runoff sample were determined, and the molar concentration ratio R of Ar and Kr was calculated. r As a physical tracer to distinguish between pre-event water and event water; S3. Construct a set of water-isotope-inert gas mass balance equations, using δ 18 The O and deuterium surplus dual isotope parameters constrain the water source mixing ratio, using R obtained in step S2. r The contribution ratio of water before the event is constrained, and the evaporation fractionation coefficient is introduced to correct the non-equilibrium enrichment of runoff isotopes; S4. Using the Markov chain Monte Carlo method, the mass balance equations are solved jointly. Given the precipitation and the total runoff determined by the corrected runoff sequence, the event water production, water production coefficient and the relative contribution rate of pre-event water and event water are output simultaneously, and the posterior probability distribution and uncertainty interval of each result are given. Among them, the δ of the water before the event in the mass balance equation set described in step S3 18 The values ​​for O and deuterium surplus are taken as the baseline isotopic values ​​of the river baseflow before the precipitation event, and the δ¹⁸O values ​​of the event water. 18 O is taken as the weighted average of the real-time precipitation sequence measured in step S1. The deuterium surplus of the event water is determined by δD and δD of the real-time precipitation sequence measured in step S1. 18 The result is calculated using O.

2. The method for simultaneous determination of watershed water yield characteristics based on isotope mass balance as described in claim 1, characterized in that, The deuterium surplus is calculated using the following method: Deuterium surplus = δD - 8 × δ 18 O.

3. The method for simultaneous determination of watershed water yield characteristics based on isotope mass balance as described in claim 2, characterized in that, The online precipitation sampler for laser water isotope spectroscopy analysis described in step S1 employs cavity ring-down spectroscopy or off-axis integrating cavity output spectroscopy technology. It directly and continuously measures δD and δD after converting liquid precipitation into water vapor via a gas-liquid film permeation method. 18 O Real-time sequence; The automatic runoff sampling unit in step S1 has a built-in colorimetric cell. The online determination of runoff suspended matter concentration to output the runoff sequence after suspended matter correction is specifically as follows: the runoff suspended matter concentration is obtained online through the colorimetric cell, and the corrected runoff sequence is output after deducting its scattering interference.

4. The method for simultaneous determination of watershed water yield characteristics based on isotope mass balance as described in claim 3, characterized in that, The molar concentration ratio R of dissolved inert gases Ar and Kr in the runoff sample during step S2. r The measurements were performed using an indoor rare gas mass spectrometer.

5. The method for simultaneous determination of watershed water yield characteristics based on isotope mass balance as described in claim 4, characterized in that, The δ of the water before the event described in step S3 18 The baseline values ​​of O and deuterium surplus in the baseflow are determined by the automatic runoff sampling unit collecting river baseflow samples before a precipitation event, and δD and δ are measured according to the method described in step S2. 18 The result was obtained after calculation.

6. The method for simultaneous determination of watershed water yield characteristics based on isotope mass balance as described in claim 5, characterized in that, The water-isotope-inert gas mass balance equations mentioned in step S3 include the following equations: Water balance equation: Q = Q e +Q p ; δ 18 O isotope mass balance equation: Q·δ 18 O r =Q e ·δ 18 O e +Q p ·δ 18 O p ; Deuterium surplus mass balance equation: Q·d r =Q e ·d e +Q p ·d p ; Mass balance equation for the molar concentration ratio of dissolved inert gases: Q·R r =Q e ·R e +Q p ·R p ; Where Q is the total runoff obtained by integrating the corrected runoff sequence; Q e For the aquatic water volume of the event; Q p This refers to the water volume of aquatic products before the incident. δ 18 O r δ for the runoff process sample measured in step S2 18 O value; δ 18 O e For the event water δ 18 O value; δ 18 O p δ of the water before the event 18 O value; d r The deuterium surplus of the runoff sample determined in step S2; d e For the deuterium surplus of the event water; d p The pre-event deuterium surplus in the water; R r The molar ratio of Ar and Kr concentrations in the runoff sample determined in step S2; R e The molar ratio of Ar and Kr concentrations in the event water; R p The ratio of the molar concentrations of Ar and Kr in water before the event.

7. The method for simultaneous determination of watershed water yield characteristics based on isotope mass balance as described in claim 6, characterized in that, The evaporation fractionation coefficient mentioned in step S3 is a correction parameter describing the non-equilibrium enrichment of isotopes caused by surface evaporation after precipitation lands and before it flows into the river channel. The evaporation fractionation coefficient is used as a variable to be solved in the mass balance equation set and is obtained by solving it together with other variables using the Markov chain Monte Carlo method.

8. The method for simultaneous determination of watershed water yield characteristics based on isotope mass balance as described in claim 7, characterized in that, The step S3, which introduces an evaporation fractionation coefficient to correct the non-equilibrium enrichment of runoff isotopes, specifically involves: in the δ 18 In the O isotope mass balance equation and the deuterium surplus mass balance equation, the δ of the event water is considered. 18 O e and d e Replace each with the value corrected for the evaporation fractionation coefficient, and the corrected δ 18 O' e and d' e Substituting the δ 18 O e The event water end-member positions in the isotopic mass balance equation and the deuterium surplus mass balance equation, replacing the original δ0 18 O e and d e : d 18 Oh e =d 18 The e +Dd 18 The evap ;d' e =d e +Δd evap ; Where, Δδ 18 O evap and Δd evap δ caused by evaporation and fractionation 18 The changes in O and deuterium surplus.

9. The method for simultaneous determination of watershed water yield characteristics based on isotope mass balance as described in claim 8, characterized in that, When solving the Markov chain Monte Carlo method in step S4, the contribution ratio of pre-event water to event water is calculated for each runoff process sample point in the mass balance equation set, thereby obtaining the dynamic change sequence of the water source contribution ratio during the entire precipitation event.