Dam leakage quantitative identification method based on multivariate hybrid model

Abstract

The invention relates to the technical field of reservoir dam leakage detection, in particular to a dam leakage quantitative identification method based on a multivariate hybrid model. According to the method, multivariate mixed model establishment analysis is carried out based on natural water chemical information, verification is further carried out in combination with isotope composition, in addition, the source position and the proportion of dam body leakage are qualitatively and quantitatively recognized in combination with mineralogical composition differences of permeable rock stratums, soil and filling materials at different positions, and the dam body leakage detection accuracy is improved. And the cause and the path of the leakage phenomenon can be more accurately and quantitatively identified.

Description

Technical Field

[0001] The present invention relates to the technical field of reservoir dam leakage detection, and in particular to a dam leakage quantitative identification method based on a multivariate mixed model. Background Art

[0002] As critical water resource regulation facilities, reservoir leakage not only affects the efficient use of water resources but also threatens the structural safety of the dam. Traditional leakage detection methods rely heavily on hydrological observation data and empirical judgment, making it difficult to accurately identify the specific cause and path of leakage. Existing dam leakage detection and identification technologies have numerous shortcomings. Visual inspection or diving surveys can only detect leakage at or near the dam surface, resulting in significant errors and susceptibility to human influence. Geophysical methods such as electrical and electromagnetic methods have limited detection depths, poor interference resistance, and are unable to determine hydraulic connections. Tracer techniques, while able to determine connectivity, cannot precisely locate leakage channels, and some techniques also pose environmental risks. Drilling methods are highly destructive, labor-intensive, and costly, and can only detect localized areas. Vibration sensor detection data processing is complex, susceptible to external interference, and has limited applicability. Hydrogen and oxygen isotope tracers have limited sampling cycles, complex model development, and limited real-time monitoring and rapid identification capabilities. Therefore, a more scientific and accurate method for quantitatively identifying dam leakage is urgently needed.

[0003] The method based on the multivariate mixed model, through comprehensive analysis of the chemical composition, mineral structure and isotopic characteristics of water bodies, rocks and soil, is expected to more accurately and quantitatively identify the causes and paths of leakage phenomena, providing strong support for dam leakage prevention and control. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a method for quantitatively identifying dam leakage based on a multivariate mixed model. The present invention can more accurately and quantitatively identify the causes and paths of leakage.

[0005] In order to achieve the above-mentioned object of the invention, the present invention provides the following technical solutions:

[0006] The present invention provides a method for quantitatively identifying dam leakage based on a multivariate mixed model, comprising the following steps: (1) conducting field exploration based on geological background survey data of the reservoir dam;

[0007] (2) Develop a sampling plan based on the field survey results;

[0008] (3) Collect samples according to the sampling plan; the samples include water samples, rock samples, soil samples and filling material samples; the water samples include seepage water samples, groundwater samples on both sides of the hillside, reservoir water samples, observation hole water samples, corridor water samples, rainwater samples and surface water samples; the rock samples include hillside and dam foundation rock samples; the soil samples include hillside and dam foundation soil samples; the filling material samples include dam foundation, dam abutment and dam body filling material samples;

[0009] (4) Detect the temperature, pH value, total dissolved solids content, anion and cation content, trace element content and isotope composition of each water sample; cations include Na + , K + , Ca 2+ and Mg 2+ , anions include Cl - 、SO4 2- 、CO3 - and HCO3 - , the trace elements include multiple ones of Li, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Sb, Ba, Be, Tl, Pb and Bi; the isotopes include one or more of hydrogen isotopes, oxygen isotopes, potassium isotopes and lithium isotopes;

[0010] Detect the mineral types and relative contents of each mineral in each rock sample, soil sample and filling material sample to obtain the mineralogical composition of each sample;

[0011] (5) performing water chemical characteristic analysis based on the temperature, pH value, total dissolved solids content, anion and cation content, and trace element content of each water sample measured in step (4), and screening possible source water sample end members that are significantly related to the leakage water;

[0012] (6) Using the anion and cation content and / or trace element content as indicators, a multivariate mixing model was constructed using Equation 1 to obtain the volume contribution ratio of the end members of each possible source of water samples in the leakage water;

[0013]

[0014] j = 1, 2, 3…k; k is the number of indicators, n is the number of end members of water samples that may be the source of leakage water, k ≥ n;

[0015] In formula 1:

[0016] C j is the value of the jth indicator in the leakage water;

[0017] x i is the volume contribution ratio of the i-th possible source of leakage water to the leakage water;

[0018] C ij is the value of the jth index in the i-th endmember;

[0019] The samples of the possible source water sample end members are mixed according to the volume contribution ratio obtained by solving the above multivariate mixing model to obtain a mixed sample; the anion and cation content and / or trace element content of the mixed sample is measured as a simulated value, and the variance ratio R between the simulated value and the measured value of the leakage water is calculated according to Formula 2 2 , recorded as the first coefficient of determination;

[0020] n is the number of indicators, and its value is the same as k in formula 1;

[0021] In formula 2, x i is the measured value of the content of anions, cations or trace elements in the leakage water, y i is the simulated value of the anion, cation or trace element content in the mixed sample, is the average value of the measured values ​​of each leakage index;

[0022] (7) verifying the isotopic characteristics of the solution obtained in step (6);

[0023] The isotope characteristic verification includes: using the isotope content of each water sample measured in step (4) as a new indicator, replacing one or more indicators in step (6), re-constructing the multivariate mixture model according to step (6), solving to obtain the volume contribution ratio of the end members of each possible source water sample, and calculating the second determination coefficient with reference to step (6);

[0024] If the absolute value of the difference between the first determination coefficient and the second determination coefficient is ≤0.35, it means that the volume contribution ratio of each possible source water sample end member in the leakage water obtained by step (6) is reasonable, and the first determination coefficient is used as the first qualified determination coefficient after verification; if the absolute value of the difference between the first determination coefficient and the second determination coefficient is greater than 0.35, it means that the result obtained by step (6) is unreasonable, and the possible source water sample end member is replaced, and the multivariate mixing model is re-constructed according to step (6) until the isotope characteristic verification is passed and the first qualified determination coefficient is obtained;

[0025] (8) According to the water chemical analysis results of step (5), replace the end members of the water samples from different possible sources, repeat steps (6) and (7), obtain a new second qualified determination coefficient verified by the isotope characteristics, compare the first qualified determination coefficient with the second qualified determination coefficient, and take the model result with the higher determination coefficient as the true volume ratio representing the source of the leakage water;

[0026] (9) Based on the actual volume proportion of the leakage source determined in step (8) and the mineralogical composition characteristics obtained in step (4), the path and channel of the dam leakage are explored and analyzed.

[0027] Preferably, the geological background survey includes engineering data on the dam's geological and topographical characteristics, stratigraphic structure, hydrogeological conditions, natural environmental factors, and layout of corridors and observation holes.

[0028] Preferably, in step (4), the method for determining the anion and cation content includes ion chromatography.

[0029] Preferably, in step (4), the method for determining the trace element content includes inductively coupled plasma mass spectrometry.

[0030] Preferably, in step (4), the hydrogen isotope is deuterium, and the oxygen isotope is 18 O, the potassium isotope is 41 K, the lithium isotope is 7 Li.

[0031] Preferably, in step (5), the screening of possible source water sample end members significantly correlated with the leakage water includes: first preliminarily analyzing the similarities and differences between the temperature, pH value, total dissolved solids content, anion and cation content, and trace element content distribution of each water sample, analyzing the hydrochemical characteristics of each water sample in combination with the geological background of the dam area, and then further using correlation analysis and principal component analysis methods to analyze the correlation between the leakage water and other water samples, and screening possible source water sample end members significantly correlated with the leakage water.

[0032] Preferably, the indicators used to construct the multivariate mixed model in step (6) include all measured anion and cation contents and trace element contents.

[0033] Preferably, in step (2), formulating a sampling plan based on the field exploration results includes: formulating a sampling plan based on the field investigation of the dam's seepage and outflow conditions, and selecting locations with different water depths and different hydrological characteristics on and around the dam for sampling.

[0034] Preferably, in step (3), the reservoir water samples include reservoir water samples at different water levels in front of the dam.

[0035] The present invention quantitatively analyzes the contribution ratio of different water sources to dam seepage water through a multivariate mixed model, providing a scientific basis for the source of the seepage water.

[0036] The accuracy of the model is ensured by isotope signature verification. Step (8) replaces the end member of the water sample that may be the source of the leakage water and optimizes the multivariate mixing model to further ensure the reliability of the analysis results.

[0037] The present invention combines the differences in mineralogical composition with the results of model optimization to clarify the path of dam leakage and provide a scientific basis for leakage prevention and control. DETAILED DESCRIPTION

[0038] The present invention provides a method for quantitatively identifying dam leakage based on a multivariate mixed model, comprising the following steps: (1) conducting field exploration based on geological background survey data of the reservoir dam;

[0039] (2) Develop a sampling plan based on the field survey results;

[0040] (3) Collect samples according to the sampling plan; the samples include water samples, rock samples, soil samples and filling material samples; the water samples include seepage water samples, groundwater samples on both sides of the hillside, reservoir water samples, observation hole water samples, corridor water samples, rainwater samples and surface water samples; the rock samples include hillside and dam foundation rock samples; the soil samples include hillside and dam foundation soil samples; the filling material samples include dam foundation, dam abutment and dam body filling material samples;

[0041] (4) Detect the temperature, pH value, total dissolved solids content, anion and cation content, trace element content and isotope composition of each water sample; cations include Na + , K + , Ca 2+ and Mg 2+ , anions include Cl - 、SO4 2- 、CO3 - and HCO3 - , the trace elements include multiple ones of Li, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Sb, Ba, Be, Tl, Pb and Bi; the isotopes include one or more of hydrogen isotopes, oxygen isotopes, potassium isotopes and lithium isotopes;

[0042] Detect the mineral types and relative contents of each mineral in each rock sample, soil sample and filling material sample to obtain the mineralogical composition of each sample;

[0043] (5) performing water chemical characteristic analysis based on the temperature, pH value, total dissolved solids content, anion and cation content, and trace element content of each water sample measured in step (4), and screening possible source water sample end members that are significantly related to the leakage water;

[0044] (6) Using the anion and cation content and / or trace element content as indicators, a multivariate mixing model was constructed using Equation 1 to obtain the volume contribution ratio of the end members of each possible source of water samples in the leakage water;

[0045]

[0046] j = 1, 2, 3…k; k is the number of indicators, n is the number of end members of water samples that may be the source of leakage water, k ≥ n;

[0047] In formula 1:

[0048] C j is the value of the jth indicator in the leakage water;

[0049] x i is the volume contribution ratio of the i-th possible source of leakage water to the leakage water;

[0050] C ij is the value of the jth index in the i-th endmember;

[0051] The samples of the possible source water sample end members are mixed according to the volume contribution ratio obtained by solving the above multivariate mixing model to obtain a mixed sample; the anion and cation content and / or trace element content of the mixed sample is measured as a simulated value, and the variance ratio R between the simulated value and the measured value of the leakage water is calculated according to Formula 2 2 , recorded as the first coefficient of determination;

[0052] n is the number of indicators, and its value is the same as k in formula 1;

[0053] In formula 2, x i is the measured value of the content of anions, cations or trace elements in the leakage water, y i is the simulated value of the anion, cation or trace element content in the mixed sample, is the average value of the measured values ​​of each leakage index;

[0054] (7) verifying the isotopic characteristics of the solution obtained in step (6);

[0055] The isotope characteristic verification includes: using the isotope content of each water sample measured in step (4) as a new indicator, replacing one or more indicators in step (6), re-constructing the multivariate mixture model according to step (6), solving to obtain the volume contribution ratio of the end members of each possible source water sample, and calculating the second determination coefficient with reference to step (6);

[0056] If the absolute value of the difference between the first determination coefficient and the second determination coefficient is ≤0.35, it means that the volume contribution ratio of each possible source water sample end member in the leakage water obtained by step (6) is reasonable, and the first determination coefficient is used as the first qualified determination coefficient after verification; if the absolute value of the difference between the first determination coefficient and the second determination coefficient is greater than 0.35, it means that the result obtained by step (6) is unreasonable, and the possible source water sample end member is replaced, and the multivariate mixing model is re-constructed according to step (6) until the isotope characteristic verification is passed and the first qualified determination coefficient is obtained;

[0057] (8) According to the water chemical analysis results of step (5), replace the end members of the water samples from different possible sources, repeat steps (6) and (7), obtain a new second qualified determination coefficient verified by the isotope characteristics, compare the first qualified determination coefficient with the second qualified determination coefficient, and take the model result with the higher determination coefficient as the true volume ratio representing the source of the leakage water;

[0058] (9) Based on the actual volume proportion of the leakage source determined in step (8) and the mineralogical composition characteristics obtained in step (4), the path and channel of the dam leakage are explored and analyzed.

[0059] The present invention first conducts a geological background survey on the reservoir dam to obtain geological background survey data.

[0060] In the present invention, the geological background survey includes collecting and obtaining engineering data on the dam's geological and topographical characteristics, stratigraphic structure, hydrogeological conditions, natural environmental factors, and the layout of corridors and observation holes. The geological background survey is conducted in the present invention to enable on-site exploration in combination with the geological background data.

[0061] After obtaining geological background survey data, the present invention conducts field exploration based on the geological background survey data and formulates a sampling plan based on the field exploration results.

[0062] The present invention has no specific requirements for the field survey process; it can be conducted according to methods well known in the art. Specifically, it includes dam inspection and groundwater level observation. For example, the dam surface is observed for abnormalities such as cracks, collapses, heaves, water seepage, soil flow, piping, and any human or biological damage. If observation holes are arranged in and around the dam foundation, changes in the groundwater level during water storage can be monitored and analyzed for their relationship to leakage. The purpose of conducting field surveys in the present invention is to better understand the nature and potential scope of leakage in light of the actual dam project, select appropriate sampling points, and develop a detailed sampling plan.

[0063] The present invention preferably develops a detailed sampling plan based on on-site investigations of dam seepage and outflow, selecting locations with varying water depths and hydrological characteristics for sampling within and around the dam. In the present invention, the sampling plan preferably ensures comprehensive coverage of possible seepage paths and impact areas.

[0064] After formulating the sampling plan, the present invention collects samples according to the sampling plan.

[0065] In the present invention, the samples include water samples, rock samples, soil samples and filling material samples; the water samples include seepage water samples, groundwater samples on both sides of the hillside, reservoir water samples, observation hole water samples, corridor water samples, rainwater samples and surface water samples; the reservoir water samples preferably include reservoir water samples at different elevations in front of the dam, more preferably the upper reservoir water, middle reservoir water and bottom reservoir water in front of the dam.

[0066] In the present invention, the rock samples include hillside and dam foundation rock samples; the soil samples include hillside and dam foundation soil samples; and the filling material samples include dam foundation, dam abutment and dam body filling material samples.

[0067] After completing the sample collection, the present invention detects the temperature, pH value, total dissolved solid content, anion and cation content, trace element content and isotope composition of each water sample; wherein, cations include Na + , K + , Ca 2+ and Mg 2+ , anions include Cl - 、SO4 2- 、CO3 - and HCO3 - The trace elements include multiple elements selected from Li, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Sb, Ba, Be, Tl, Pb and Bi; the isotopes include multiple elements selected from hydrogen isotopes, oxygen isotopes, potassium isotopes and lithium isotopes; the hydrogen isotope is preferably deuterium, and the oxygen isotope is preferably 18 O, the potassium isotope is preferably 41 K, the lithium isotope is preferably 7 Li.

[0068] The present invention provides basic data for subsequent analysis through temperature measurement; understands the chemical environment of the water body through pH value determination; evaluates the mineralization degree of the water body through total dissolved solids (TDS) content determination; analyzes the ion composition characteristics of the water body through anion and cation content determination; and provides clues for tracing the source through trace element content determination.

[0069] The present invention preferably uses a conductivity meter to determine the total dissolved solids content in the water sample. In the present invention, the method for determining the anion and cation content preferably includes ion chromatography; the method for determining the trace element content preferably includes inductively coupled plasma mass spectrometry (ICP-MS).

[0070] In the present invention, the temperature, pH value, total dissolved solids content, anion and cation content, and trace element content of the water sample are used for subsequent water chemical characteristic analysis to screen possible source water sample end members that are significantly correlated with leakage water; the isotopic composition of the water sample is used for subsequent isotopic characteristic verification of the multivariate mixing model.

[0071] The present invention detects the mineral types of various rock samples, soil samples and filling material samples and the relative content of various minerals in the samples to obtain the mineralogical composition of each sample.

[0072] The present invention has no specific requirements for the detection methods of the mineral species and relative contents; detection methods well known in the art can be employed, such as X-ray diffraction (XRD) to identify the mineral species and relative contents in rock, soil, and fill material samples. By determining the mineral species and relative contents, the present invention reveals the mineral composition characteristics of different regions, providing a basis for determining leakage paths.

[0073] After completing the water sample test, the present invention performs water chemical characteristic analysis based on the measured temperature, pH value, total dissolved solids content, anion and cation content, and trace element content of each water sample to screen possible source water sample end members that are significantly related to the leakage water.

[0074] The present invention preferably first preliminarily analyzes the differences and similarities (i.e., differences and similarities) between the temperature, pH value, TDS, anion and cation content, and trace element content distribution of each water sample, combines the geological background of the dam area, analyzes the hydrochemical characteristics of each water sample, and then further uses correlation analysis and principal component analysis methods to analyze the correlation between the leakage water and other water samples, and screens the possible source water sample end members that are significantly correlated with the leakage water.

[0075] The present invention has no special requirements on the number of water sample end members that may be the source of the leaking water. The number can be selected according to actual conditions and may be 4, 5 or more.

[0076] In the present invention, the correlation analysis and principal component analysis methods are well-known methods in the art and will not be discussed in detail here.

[0077] After screening out the possible source water sample end members significantly related to the leakage water, the present invention uses the anion and cation content and / or trace element content as indicators to construct a multivariate mixed model using Formula 1 to solve for the volume contribution ratio of each possible source water sample end member in the leakage water;

[0078]

[0079] j = 1, 2, 3…k; k is the number of indicators, n is the number of end members of water samples that may be the source of leakage water, k ≥ n;

[0080] In formula 1:

[0081] C j is the value of the jth indicator in the leakage water;

[0082] x i is the volume contribution ratio of the i-th possible source of leakage water to the leakage water;

[0083] C ij is the value of the jth index in the ith endmember.

[0084] In the present invention, when building mixed multivariate model, the number of indicators needs ≥ the number of the possible source water sample end members of leakage water; Suppose, after analysis, leakage water may be mixed according to a certain ratio x1, x2, x3, x4 by reservoir water, left bank hillside groundwater, right bank hillside groundwater and other possible source samples, then the number of the possible source water sample end members of leakage water is 4, so the required index for building multivariate mixed model should be ≥4, these indicators can be selected from anion and cation content and / or trace element content, therefrom at least 4 kinds of indicators are selected for building mixed model, the present invention preferably selects the anion and cation content of all measurements and the trace element content as the index of multivariate mixed model. For example, the present invention measured 26 kinds of anions and cations and trace element (i.e., the kind of anions and cations and trace elements is 26 kinds) content in the early stage, then preferably adopts the content of these 26 kinds of anions and cations and trace elements as index for building multivariate mixed model.

[0085] In the present invention, when constructing a multivariate mixed model, the constraints are: x1+x2+…+x n ≤1.

[0086] After solving for the volume contribution ratio of each possible source water sample end member in the leakage water, the present invention mixes the samples of the possible source water sample end members according to the volume contribution ratio obtained by solving the above multivariate mixing model to obtain a mixed sample; the anion and cation content and / or trace element content of the mixed sample is measured as a simulated value, and the variance ratio R between the simulated value and the measured value of the leakage water is calculated according to Formula 2 2 , recorded as the first coefficient of determination;

[0087] n is the number of indicators, and its value is the same as k in formula 1;

[0088] In formula 2, x i is the measured value of the content of anions, cations or trace elements in the leakage water, y i is the simulated value of the anion, cation or trace element content in the mixed sample, It is the average value of the measured values ​​of various leakage indicators.

[0089] The present invention obtains a first determination coefficient through simulation experiments for subsequent isotope characteristic verification.

[0090] After obtaining the first determination coefficient, the present invention verifies the isotopic characteristics of the solution obtained in step (6).

[0091] In the present invention, the isotope characteristic verification includes: using the isotope content of each water sample measured in step (4) as a new indicator, replacing one or more indicators in step (6), re-constructing the multivariate mixing model according to step (6), solving to obtain the volume contribution ratio of the end members of each possible source water sample, and calculating the second determination coefficient with reference to step (6).

[0092] In the present invention, the process of constructing a multivariate mixture model using isotope content as an indicator is the same as above, the only difference being that the indicator (originally the anion and cation content and / or trace element content) is replaced by the isotope content.

[0093] In the present invention, if the absolute value of the difference between the first determination coefficient and the second determination coefficient is ≤0.35, it means that the volume contribution ratio of the end members of the water samples from each possible source in the leakage water obtained by step (6) is reasonable, and the first determination coefficient is used as the first qualified determination coefficient after verification; if the absolute value of the difference between the first determination coefficient and the second determination coefficient is greater than 0.35, it means that the result obtained by step (6) is unreasonable, the end members of the water samples from the possible source are replaced, and the multivariate mixing model is reconstructed according to step (6) until the isotope characteristic verification is passed and the first qualified determination coefficient is obtained.

[0094] After obtaining the first qualified determination coefficient, the present invention replaces the end members of water samples from different possible sources based on the water chemical analysis results of step (5) (i.e., the temperature, pH value, total dissolved solids content, anion and cation content, and trace element content analysis results of each water sample), repeatedly constructs the multivariate mixing model and isotope characteristic verification, and obtains a new second qualified determination coefficient that passes the isotope characteristic verification. The first qualified determination coefficient and the second qualified determination coefficient are compared, and the model result with the higher determination coefficient is used as the true volume proportion representing the source of the leakage water.

[0095] The present invention ensures the accuracy of the model through isotope signature verification, replaces the end members of the water sample that may be the source of the leakage water, and optimizes the multivariate mixing model to further ensure the reliability of the analysis results.

[0096] After obtaining the actual volume proportion of the leakage source, the present invention explores and analyzes the path channel of the dam leakage based on the determined actual volume proportion of the leakage source and the mineralogical composition characteristics obtained above.

[0097] Since the reservoir water seeps through different rock layers or materials from the dam panel, the mountains on both sides, and the dam foundation, the path of dam leakage can be explored and analyzed based on the actual volume proportion of the leakage water source and the mineralogical composition characteristics of the rock, soil, dam foundation, dam shoulder and dam filling material samples at different locations obtained previously.

[0098] The quantitative identification method for dam leakage based on the multivariate mixed model provided by the present invention is described in detail below with reference to the embodiments, but they should not be construed as limiting the scope of protection of the present invention.

[0099] Example 1

[0100] For example, during the initial filling of a hydropower station, water leakage was discovered. Based on the geological background survey and field exploration results, a specific sampling plan was developed. A total of 54 water samples were collected, including leakage water, upstream reservoir water, simulated over-dam leakage water, observation hole and right bank corridor water, and other possible water samples (rainwater, surface water). In addition, four rock samples, two soil samples, and one dam material sample were collected for chemical, isotopic, and mineralogical analysis.

[0101] Analysis of water chemistry revealed multiple sources of seepage water, including the possibility of leakage from upstream reservoirs. Furthermore, the water was influenced by multiple factors, including the interaction between external high-Li-content water sources and geological media. End members were selected based on the correlation between seepage water and other water samples, and the representative end member samples selected were as follows: surface reservoir water: left-dam body-0, middle-dam body-0, right-dam body-0, left-3175-0, middle-3175-0, right-3175-0, and middle-3086-0, taking the average value; middle reservoir water: left-3175-70, middle-3175-70, right-3175-70, and middle-3086-70, taking the average value; deep reservoir water: middle-3086-120; right bank hillside water: OH11; left bank hillside water: OH6; right bank pressure measuring tube hole 3240 elevation: Er-3; right bank 3190 elevation: OH19; left bank 3225 elevation: OH4; left bank traffic hole 3120 elevation: ZSD and JTF, taking the average value; left bank traffic hole 3094 elevation: FSD.

[0102] A multivariate mixing model for seepage water was established. Representative end-point metadata was loaded, and the contents of Li, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Sb, Ba, Be, Tl, Pb, and Bi were selected as indicators for model calculation. The coefficient of determination between the simulated and measured values ​​was calculated based on the model results, and was found to be 0.7298.

[0103] Isotope signature verification. Combined with isotope parameters (specifically deuterium and 18 O content), establish a seepage water end-member mixing model, quantitatively analyze the possible sources and their proportion in the leakage, and compare and verify with the results of step 7. The determination coefficient obtained by isotope verification is 0.7890, which shows that the results are basically consistent, and the main source is reservoir water, followed by left bank seepage.

[0104] The model was further optimized and the coefficient of determination was calculated by replacing different end members (replacing the average value of the ZSD and JTF values ​​at the 3120 elevation of the left bank access tunnel with the average value of the GBD and JTF values ​​at the 3120 elevation of the left bank access tunnel). The results showed that the optimized coefficient of determination was 0.9650, higher than the original coefficient of determination of 0.7298, indicating that the optimized component percentages can more accurately reflect the source of water leakage from the measuring weir.

[0105] Therefore, the composition of seepage water is: 26.16% surface reservoir water, 38.85% middle reservoir water, 16.90% deep reservoir water, 9.90% left bank seepage, 6.31% left bank seepage, and other less than 5% left and right bank seepage and hillside water.

[0106] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A quantitative identification method for dam leakage based on a multivariate mixture model, characterized in that: The following steps are involved: (1) Conduct field exploration based on the geological background survey data of the reservoir and dam; (2) Develop a sampling plan based on the field survey results; (3) Collect samples according to the sampling plan; the samples include water samples, rock samples, soil samples and filling material samples; the water samples include seepage water samples, groundwater samples on both sides of the hillside, reservoir water samples, observation hole water samples, corridor water samples, rainwater samples and surface water samples; the rock samples include hillside and dam foundation rock samples; the soil samples include hillside and dam foundation soil samples; the filling material samples include dam foundation, dam abutment and dam body filling material samples; (4) Detect the temperature, pH value, total dissolved solids content, anion and cation content, trace element content and isotope composition of each water sample; cations include Na + , K + , Ca 2+ and Mg 2+ , anions include Cl - 、SO4 2- 、CO3 - and HCO3 - , the trace elements include multiple ones of Li, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Sb, Ba, Be, Tl, Pb and Bi; the isotopes include one or more of hydrogen isotopes, oxygen isotopes, potassium isotopes and lithium isotopes; Detect the mineral types and relative contents of each mineral in each rock sample, soil sample and filling material sample to obtain the mineralogical composition of each sample; (5) performing water chemical characteristic analysis based on the temperature, pH value, total dissolved solids content, anion and cation content, and trace element content of each water sample measured in step (4), and screening possible source water sample end members that are significantly related to the leakage water; (6) Using the anion and cation content and / or trace element content as indicators, a multivariate mixture model was constructed using Equation 1 to obtain the volume contribution ratio of the end members of each possible source of water samples in the leakage water; j = 1, 2, 3…k; k is the number of indicators, n is the number of end members of water samples that may be the source of leakage water, k ≥ n; In formula 1: C j is the value of the jth indicator in the leakage water; x i is the volume contribution ratio of the i-th possible source of leakage water to the leakage water; C ij is the value of the jth index in the i-th endmember; The samples of the possible source water sample end members are mixed according to the volume contribution ratio obtained by solving the above multivariate mixing model to obtain a mixed sample; the anion and cation content and / or trace element content of the mixed sample is measured as a simulated value, and the variance ratio R between the simulated value and the measured value of the leakage water is calculated according to Formula 2 2 , recorded as the first coefficient of determination; n is the number of indicators, and its value is the same as k in formula 1; In formula 2, x i is the measured value of the anion, cation or trace element content in the leakage water, y i is the simulated value of the anion, cation or trace element content in the mixed sample, is the average value of the measured values ​​of each leakage index; (7) verifying the isotopic characteristics of the solution obtained in step (6); The isotope characteristic verification includes: using the isotope content of each water sample measured in step (4) as a new indicator, replacing one or more indicators in step (6), re-constructing the multivariate mixture model according to step (6), solving to obtain the volume contribution ratio of the end members of each possible source water sample, and calculating the second determination coefficient with reference to step (6); If the absolute value of the difference between the first determination coefficient and the second determination coefficient is ≤0.35, it means that the volume contribution ratio of each possible source water sample end member in the leakage water obtained by step (6) is reasonable, and the first determination coefficient is used as the first qualified determination coefficient after verification; if the absolute value of the difference between the first determination coefficient and the second determination coefficient is greater than 0.35, it means that the result obtained by step (6) is unreasonable, and the possible source water sample end member is replaced, and the multivariate mixing model is re-constructed according to step (6) until the isotope characteristic verification is passed and the first qualified determination coefficient is obtained; (8) According to the water chemical analysis results of step (5), replace the end members of the water samples from different possible sources, repeat steps (6) and (7), obtain a new second qualified determination coefficient verified by the isotope characteristics, compare the first qualified determination coefficient with the second qualified determination coefficient, and take the model result with the higher determination coefficient as the true volume ratio representing the source of the leakage water; (9) Based on the actual volume proportion of the leakage source determined in step (8) and the mineralogical composition characteristics obtained in step (4), the path and channel of the dam leakage are explored and analyzed.

2. The method for quantitatively identifying dam leakage according to claim 1, characterized in that: The geological background survey includes engineering data on the dam's geological and topographical characteristics, stratigraphic structure, hydrogeological conditions, natural environmental factors, and the layout of corridors and observation holes.

3. The method for quantitatively identifying dam leakage according to claim 1, characterized in that: In step (4), the method for determining the anion and cation content includes ion chromatography.

4. The method for quantitatively identifying dam leakage according to claim 1, characterized in that: In step (4), the method for determining the trace element content includes inductively coupled plasma mass spectrometry.

5. The method for quantitatively identifying dam leakage according to claim 1, characterized in that: In step (4), the hydrogen isotope is deuterium, and the oxygen isotope is 18 O, the potassium isotope is 41 K, the lithium isotope is 7 Li.

6. The method for quantitatively identifying dam leakage according to claim 1, characterized in that: In step (5), the screening of possible source water sample end members significantly correlated with the leakage water includes: first preliminarily analyzing the similarities and differences between the temperature, pH value, total dissolved solids content, anion and cation content, and trace element content distribution of each water sample, combining the geological background of the dam area, analyzing the hydrochemical characteristics of each water sample, and then further using correlation analysis and principal component analysis methods to analyze the correlation between the leakage water and other water samples, and screening possible source water sample end members significantly correlated with the leakage water.

7. The method for quantitatively identifying dam leakage according to claim 1, characterized in that: The indicators used to construct the multivariate mixed model in step (6) include all measured anion and cation contents and trace element contents.

8. The method for quantitatively identifying dam leakage according to claim 1, characterized in that: In step (2), formulating a sampling plan based on the field survey results includes: formulating a sampling plan based on the field investigation of the dam's seepage and outflow conditions, and selecting locations with different water depths and different hydrological characteristics on and around the dam for sampling.

9. The method for quantitatively identifying dam leakage according to claim 1, characterized in that: In step (3), the reservoir water samples include reservoir water samples at different water levels in front of the dam.

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