A dam leakage quantitative identification method based on a multi-component mixture model

Abstract

The present application relates to the technical field of reservoir dam leakage detection, and particularly relates to a dam leakage quantitative identification method based on a multivariate mixed model. The present application is based on natural water chemical information to establish and analyze a multivariate mixed model, and further verifies the model by combining isotope composition. In addition, by combining the mineralogical composition differences of water-permeable rock layers and soil and filling materials at different positions, the source position and proportion of dam body leakage can be qualitatively and quantitatively identified, so that the causes and paths of the leakage phenomenon can be more accurately quantitatively identified.

Description

TECHNICAL FIELD

[0001] The present application 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

[0002] As a key water resource regulation facility, the leakage of a reservoir not only affects the effective use of water resources, but also may endanger the safety of the dam structure. Traditional leakage detection methods rely mainly on hydrological observation data and experience-based judgment, which makes it difficult to accurately identify the specific causes and paths of leakage. Existing dam leakage detection and identification technologies have many shortcomings. Visual inspection or diving exploration can only detect surface or near-surface leakage, with large errors and being easily affected by human factors; geophysical methods such as electrical and electromagnetic methods have limited detection depth, poor anti-interference ability, and cannot determine hydraulic connections; tracer technology can determine connectivity, but cannot accurately determine the location of the leakage path, and some techniques also have environmental risks; drilling methods are highly destructive, have large workloads and high costs, and can only detect locally; vibration sensor detection data processing is complex, susceptible to external interference, and has limited scope of application; hydrogen and oxygen isotope tracer sampling cycles are limited, model establishment is complex, and real-time monitoring and rapid identification capabilities are insufficient. Therefore, there is an urgent need for a more scientific and accurate dam leakage quantitative identification method.

[0003] Based on the multivariate mixed model method, by comprehensively analyzing the chemical composition, mineral structure and isotope characteristics of water, rock and soil, it is expected to more accurately quantitatively identify the causes and paths of leakage phenomena, and to provide strong support for dam leakage prevention and control. SUMMARY

[0004] Therefore, the purpose of the present application is to provide a dam leakage quantitative identification method based on a multivariate mixed model. The present application can more accurately quantitatively identify the causes and paths of leakage phenomena.

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

[0006] The present application provides a dam leakage quantitative identification method based on a multivariate mixed model, comprising the following steps: (1) conducting field exploration according to the geological background investigation data of the reservoir dam;

[0007] (2) developing a sampling scheme according to the field exploration results;

[0008] (3) according to the sampling scheme to collect samples; the samples include water samples, rock samples, soil samples and filling material samples; the water samples include seepage water samples, cross-river slope groundwater samples, reservoir water samples, observation hole water samples, gallery water samples, rainwater samples and surface water samples; the rock samples include slope and dam foundation rock samples; the soil samples include slope and dam foundation soil samples; the filling material samples include dam foundation, dam shoulder and dam body filling material samples;

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

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

[0011] (5) performing water chemical characteristic analysis according to the temperature, pH value, total dissolved solid content, anion and cation content and trace element content of each water sample determined in step (4) to screen possible source water sample end members significantly related to seepage water;

[0012] (6) taking the anion and cation content and / or trace element content as an index, constructing a multivariate mixing model by using formula 1 to obtain the volume contribution proportion of each possible source water sample end member in seepage water;

[0013]

[0014] j = 1, 2, 3…k; k is the number of indexes, n is the number of seepage water possible source water sample end members, and k≥n;

[0015] In formula 1:

[0016] C j is the value of the jth index in seepage water;

[0017] x i is the volume contribution proportion of the ith seepage water possible source end member to seepage water;

[0018] C ij is the value of the jth index in the ith end-member;

[0019] The sample of the end-member of the possible source water sample is mixed according to the volume contribution ratio obtained by solving the multivariate mixture model to obtain a mixed sample; the anion and cation content and / or trace element content of the mixed sample is determined as a simulation value, and the variance ratio R between the simulation value and the measured value of the leakage water is calculated according to formula 2 2 , denoted as the first determination coefficient;

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

[0021] 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 simulation value of the anion, cation or trace element content in the mixed sample, is the average value of the measured values of the indexes of the leakage water;

[0022] (7) The solution result of step (6) is verified by isotope characteristics;

[0023] The isotope characteristic verification includes: taking the isotope content of each water sample measured in step (4) as a new index, replacing one or more indexes in step (6), and re-constructing a multivariate mixture model according to step (6) to obtain the volume contribution ratio of each possible source water sample end-member, and calculating a second determination coefficient according 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 result of each possible source water sample end-member in the leakage water obtained by solving step (6) is reasonable, and the verification is passed, then the first determination coefficient is taken as the first qualified determination coefficient; if the absolute value of the difference between the first determination coefficient and the second determination coefficient is >0.35, it means that the result obtained by solving step (6) is unreasonable, the possible source water sample end-member is replaced, and a multivariate mixture 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 result of step (5), the different possible source water sample end-member is replaced, and steps (6) and (7) are repeated to obtain a new second qualified determination coefficient which passes the isotope characteristic verification, and the model result with a high determination coefficient is taken as the real volume ratio of the leakage water source;

[0026] (9) According to the real volume ratio of the leakage water source determined in step (8), combined with the mineralogical composition characteristics obtained in step (4), the path channel of the dam body leakage is explored and analyzed.

[0027] Preferably, the geological background investigation includes dam geological topographic features, stratigraphic structure, hydrogeological conditions, natural environmental factors, gallery and observation hole layout engineering data.

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

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

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

[0031] Preferably, in step (5), the screening of the water sample end member of the possible source significantly related to the seepage water includes: first, analyzing the similarities and differences between the temperature, pH value, total dissolved solid content, anion and cation content, and trace element content distribution of each water sample, combining with the dam area geological background, analyzing the water chemical characteristics of each water sample, and then further analyzing the correlation between the seepage water and other water samples by using correlation analysis and principal component analysis method, and screening the water sample end member of the possible source significantly related to the seepage water.

[0032] Preferably, in step (6), the index used for constructing the multivariate mixture model includes all the determined anion and cation content and trace element content.

[0033] Preferably, in step (2), the sampling scheme is formulated according to the field exploration results, including: according to the seepage outflow of the dam, formulating a sampling scheme, and sampling at positions with different water depths and different hydrological characteristics around the dam body.

[0034] Preferably, in step (3), the library water sample includes dam front water samples at different elevations.

[0035] The present application quantitatively analyzes the contribution proportion of different water sources to the dam seepage water by using a multivariate mixture model, and provides a scientific basis for the source of the seepage water.

[0036] The accuracy of the model is ensured through isotope characteristic verification, the seepage water possible source water sample end member is replaced in step (8), the multivariate mixture model is optimized, and the reliability of the analysis result is further ensured.

[0037] The present application combines the mineralogical composition difference and the model optimization result, and clearly determines the seepage path of the dam body, and provides a scientific basis for seepage prevention and control. DETAILED DESCRIPTION

[0038] The application provides a dam leakage quantitative identification method based on a multivariate mixture model, comprising the following steps: (1) performing field exploration according to the geological background investigation data of a reservoir dam;

[0039] (2) formulating a sampling scheme according to the field exploration results;

[0040] (3) collecting samples according to the sampling scheme; the samples comprise water samples, rock samples, soil samples and filling material samples; the water samples comprise leakage water samples, both-bank slope groundwater samples, reservoir water samples, observation hole water samples, gallery water samples, rainwater samples and surface water samples; the rock samples comprise slope and dam foundation rock samples; the soil samples comprise slope and dam foundation soil samples; and the filling material samples comprise dam foundation, dam shoulder and dam body filling material samples;

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

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

[0043] (5) performing water chemical characteristic analysis according to the temperature, pH value, total dissolved solid content, anion and cation content and trace element content of each water sample determined in step (4) to screen possible source water sample end members significantly related to leakage water;

[0044] (6) taking the anion and cation content and / or trace element content as indexes, constructing a multivariate mixture model by using formula 1, and solving to obtain the volume contribution proportion of each possible source water sample end member in leakage water;

[0045]

[0046] j=1, 2, 3…k; k is the number of indexes, n is the number of possible source water sample end members of leakage water, and k≥n;

[0047] In formula 1,

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

[0049] x i is the volume contribution ratio of the ith leakage water possible source end member to the leakage water;

[0050] C ij is the value of the jth index in the ith end member;

[0051] The sample of the possible source water sample end member is mixed according to the volume contribution ratio obtained by solving the multivariate mixture model to obtain a mixed sample; the anion and cation content and / or trace element content of the mixed sample are determined as simulation values, and the variance ratio R between the simulation values and the measured values of the leakage water is calculated according to formula 2 2 , which is the first determination coefficient;

[0052] n is the number of indexes, which has the same value as k in formula 1;

[0053] 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 simulation value of the anion, cation or trace element content in the mixed sample, is the average value of the measured values of the indexes of the leakage water;

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

[0055] The isotopic characteristic verification includes: taking the isotopic content of each water sample measured in step (4) as a new index, replacing one or more indexes in step (6), and re-constructing the multivariate mixture model according to step (6) to obtain the volume contribution ratio of each possible source water sample end member, and calculating the second determination coefficient according 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 solving step (6) is reasonable, and the verification is passed, then the first determination coefficient is the first qualified determination coefficient; if the absolute value of the difference between the first determination coefficient and the second determination coefficient is >0.35, it means that the result obtained by solving step (6) is unreasonable, the possible source water sample end member is replaced, and the multivariate mixture model is re-constructed according to step (6) until the isotopic characteristic verification is passed, and the first qualified determination coefficient is obtained;

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

[0058] (9) Based on the actual volume ratio of the seepage source determined in step (8), and combined with the mineralogical composition characteristics obtained in step (4), explore and analyze the path and channel of seepage in the dam body.

[0059] This invention first conducts a geological background survey of the reservoir dam to obtain geological background survey data.

[0060] In this invention, the geological background survey includes collecting engineering data on the dam's geological and topographical features, stratigraphic structure, hydrogeological conditions, natural environmental factors, and the layout of corridors and observation wells. The geological background survey in this invention is conducted to enable on-site exploration in conjunction 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] This invention does not impose special requirements on the on-site exploration process; it can be conducted using methods well-known in the art, specifically including dam body inspection and groundwater level monitoring. For example, observing whether abnormal phenomena such as cracks, collapses, heaves, seepage, soil erosion, and piping appear on the dam surface, and whether there is any human or biological damage. If observation wells are arranged in and around the dam foundation, the changes in groundwater level during water impoundment are monitored, and their relationship with seepage is analyzed. In this invention, the purpose of conducting on-site exploration is to better understand the situation and potential range of seepage in the dam project, in conjunction with the actual conditions of the dam, to better select appropriate sampling points, and thus to formulate a detailed sampling plan.

[0063] This invention preferably develops a detailed sampling plan based on on-site investigation of the dam's seepage flow, selecting locations with different water depths and hydrological characteristics within and around the dam body. In this invention, the sampling plan preferably comprehensively covers all possible seepage paths and their impact range.

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

[0065] In this invention, the samples include water samples, rock samples, soil samples, and filling material samples; the water samples include seepage water samples, groundwater samples from both sides of the hillside, reservoir water samples, observation well 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, and more preferably upper reservoir water, middle reservoir water, and bottom reservoir water in front of the dam.

[0066] In the present application, 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 shoulder and dam body filling material samples.

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

[0068] The present application 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 solid (TDS) content determination, analyzes the ion composition characteristics of the water body through anion and cation content determination, and provides clues for tracing through trace element content determination.

[0069] The present application preferably determines the total dissolved solid content in the water sample by using a conductivity meter. In the present application, the determination method of the anion and cation content preferably includes ion chromatography; and the determination method of the trace element content preferably includes inductively coupled plasma mass spectrometry (ICP-MS).

[0070] In the present application, the temperature, pH value, total dissolved solid 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 significantly related to the leakage water; and the isotope composition of the water sample is used for subsequent verification of the isotope characteristics of the multivariate mixing model.

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

[0072] The present application does not have special requirements for the detection method of the mineral species and relative content, and the detection method known in the art can be used, for example, X-ray diffraction (XRD) is used to identify the mineral species and relative content in rock, soil sample and filling material sample. The present application discloses the mineral composition characteristics of different regions by determining the mineral species and relative content, thereby providing a basis for judging the leakage path.

[0073] After the test of the water sample is completed, the present application analyzes the water chemical characteristics according to the determined temperature, pH value, total dissolved solid content, anion and cation content and trace element content of each water sample, and screens the possible source water sample end member significantly related to the leakage water.

[0074] The present application preferably preliminarily analyzes the similarities and differences (i.e. differences and similarities) between the temperature, pH value, TDS, anion and cation content and trace element content distribution of each water sample, analyzes the water chemical characteristics of each water sample in combination with the dam area geological background, and then further analyzes the correlation between the leakage water and other water samples by using correlation analysis and principal component analysis method, and screens the possible source water sample end member significantly related to the leakage water.

[0075] The present application does not have special requirements for the number of possible source water sample end member of the leakage water, which can be selected according to the actual situation, and can be 4, 5 or more.

[0076] In the present application, the correlation analysis and principal component analysis method belong to the method known in the art, which will not be discussed here.

[0077] After the possible source water sample end member significantly related to the leakage water is screened, the present application uses the anion and cation content and / or trace element content as an index, uses formula 1 to construct a multivariate mixture model, and solves to obtain 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 indexes, n is the number of possible source water sample end member of the leakage water, and k≥n;

[0080] In formula 1,

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

[0082] x i is the volume contribution ratio of the ith possible source end member of the leakage water;

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

[0084] In the present application, when constructing the mixed multi-element model, the number of indexes needs to be ≥ the number of water sample end members of possible seepage water sources; assuming that the analyzed seepage water is mixed by reservoir water, left bank mountain slope groundwater, right bank mountain slope groundwater and other possible source samples according to certain proportions x1, x2, x3 and x4, then the number of water sample end members of possible seepage water sources is 4, so the indexes required for constructing the multi-element mixed model should be ≥ 4, these indexes can be selected from the cation and / or anion content and / or trace element content, at least 4 indexes are selected from them to construct the mixed model, and the present application preferably selects all the determined cation and / or anion content and trace element content as the indexes of the multi-element mixed model. For example, 26 kinds of cation and / or anion and trace element contents (i.e. the types of cation and / or anion and trace element are 26) are determined in the early stage of the present application, and the contents of the 26 kinds of cation and / or anion and trace element are preferably used as the indexes for constructing the multi-element mixed model.

[0085] In the present application, when constructing the multi-element mixed model, the constraint condition is: x1+x2+…+x n ≤1.

[0086] After obtaining the volume contribution proportion of each possible source water sample end member in the seepage water, the present application mixes the samples of the possible source water sample end members according to the volume contribution proportion obtained by the above multi-element mixed model to obtain a mixed sample; the cation and / or anion content and / or trace element content of the mixed sample is determined as the simulation value, and the variance ratio R between the simulation value and the measured value of the seepage water is calculated according to formula 2 2 , which is called the first determination coefficient;

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

[0088] In formula 2, x i is the measured value of the anion, cation or trace element content in the seepage water, y i is the simulation value of the anion, cation or trace element content in the mixed sample, is the average value of the measured values of each index of the seepage water.

[0089] The present application obtains the first determination coefficient through simulation experiments, which is used for subsequent isotope characteristic verification.

[0090] After obtaining the first determination coefficient, the present application verifies the solving results of step (6) for isotope characteristics.

[0091] In the present application, the isotope characteristic verification includes: taking the isotope content of each water sample measured in step (4) as a new index, replacing one or more indexes in step (6), re-constructing a multivariate mixture model according to step (6), solving the volume contribution ratio of each possible source water sample end member, and calculating a second determination coefficient according to step (6).

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

[0093] In the present application, 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 solved in step (6) is reasonable, and the verification is passed, so the first determination coefficient is taken as the first qualified determination coefficient; if the absolute value of the difference between the first determination coefficient and the second determination coefficient is >0.35, it means that the result solved in step (6) is unreasonable, and the possible source water sample end member is replaced, and a multivariate mixture model is re-constructed 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 application replaces different possible source water sample end members according to the water chemical analysis results (i.e. temperature, pH value, total dissolved solid content, cation and anion content, and trace element content analysis results) of step (5), repeatedly constructs a multivariate mixture model and performs isotope characteristic verification, obtains a second qualified determination coefficient that passes the isotope characteristic verification, and compares the first qualified determination coefficient and the second qualified determination coefficient, and takes the model result with a higher determination coefficient as the real volume ratio of the leakage water source.

[0095] The present application ensures the accuracy of the model through isotope characteristic verification, optimizes the multivariate mixture model by replacing the possible source water sample end member of the leakage water, and further ensures the reliability of the analysis result.

[0096] After obtaining the real volume ratio of the leakage water source, the present application combines the determined real volume ratio of the leakage water source with the mineralogical composition characteristics obtained in the foregoing to explore and analyze the path channel of the dam body leakage.

[0097] Since the rock layers or materials through which the reservoir water seeps from the dam panel, the left and right side mountains, and the dam foundation are different, therefore, according to the real volume ratio of the leakage water source, combined with the mineralogical composition characteristics of the rock, soil, dam foundation, dam shoulder, and dam filling material samples at different positions obtained in the foregoing, the path channel of the dam body leakage can be explored and analyzed.

[0098] The dam leakage quantitative identification method based on the multi-element mixed model provided by the present application will be described in detail below in combination with examples, but they cannot be understood as limiting the protection scope of the present application.

[0099] Example 1

[0100] Taking a certain hydropower station as an example, it is found that there is reservoir water leakage during the initial reservoir impoundment. For this purpose, a specific sampling scheme is developed according to the results of geological background investigation and field exploration. A total of 54 water samples are collected, including leakage water samples, upstream reservoir water samples, dam leakage simulation water samples, observation hole and right bank gallery water samples, and other possible water samples (rainwater, surface water). In addition, 4 rock samples, 2 soil samples and 1 dam material sample are collected for chemical analysis, isotope analysis and mineralogical analysis.

[0101] The water chemical characteristics analysis shows that the leakage water has multiple sources. The leakage water may come from the upstream reservoir water leakage, and is also affected by multiple factors such as external high Li content water source and geological medium interaction. According to the correlation between the leakage water and other water samples, the representative end member samples are selected 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 average value; middle layer reservoir water: left-3175-70, middle-3175-70, right-3175-70, and middle-3086-70 average value; deep layer reservoir water: middle-3086-120; right bank slope water: OH11; left bank slope water: OH6; right bank piezometer hole 3240 elevation: two-3; right bank 3190 elevation: OH19; left bank 3225 elevation: OH4; left bank traffic tunnel 3120 elevation: ZSD, JTF average value; left bank traffic tunnel 3094 elevation: FSD.

[0102] A multi-element mixed model of leakage water is established. The representative end member data is loaded, and the contents of Li, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Sb, Ba, Be, Tl, Pb and Bi are selected as indexes for model calculation. Further, the determination coefficient between the simulated value and the measured value is calculated as 0.7298 according to the model results.

[0103] Isotope characteristics verification. The isotope parameters (specifically the contents of deuterium and 18 O), the leakage water end member mixed model is established, the possible sources and their proportions in leakage are quantitatively analyzed, and the results are compared and verified with the results of step 7. The determination coefficient obtained by isotope verification is 0.7890, and the results show that they basically agree, mainly from reservoir water, and secondly from left bank bypass leakage.

[0104] The model was further optimized by replacing different end members (replacing the average of left bank traffic hole 3120 elevation: ZSD, JTF with the average of left bank traffic hole 3120 elevation: GBD, JTF) and the determination coefficient was calculated. The results show that the determination coefficient after optimization is 0.9650, higher than the determination coefficient before optimization 0.7298, indicating that the percentage of each component after optimization can more truly reflect the source proportion of the seepage water of the measuring weir.

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

[0106] The above only describes the preferred embodiments of the present application, and it should be noted that for ordinary skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should be considered as the protection scope of the present application.

Claims

1. A method for quantitative identification of dam leakage based on a multivariate hybrid model, characterized in that, Includes the following steps: (1) Conduct on-site exploration based on geological background survey data of reservoir dams; (2) Develop a sampling plan based on the results of the field exploration; (3) Samples are collected 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 from both sides of the hillside, reservoir water samples, observation well 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 isotopic composition of each water sample; among which, cations include Na + K + Ca 2+ and Mg 2+ Anions include Cl. - SO4 2- CO3 - and HCO3 - The trace elements include multiples 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. The mineral types and relative content of each mineral in the rock, soil and fill material samples were analyzed to obtain the mineralogical composition of each sample. (5) Based on the temperature, pH value, total dissolved solids content, anion and cation content and trace element content of each water sample determined in step (4), perform water chemical characteristic analysis and screen out possible source water sample end members that are significantly related to leakage water. (6) Using the content of anions and cations and / or the content of trace elements as indicators, a multivariate mixed model is constructed using Equation 1 to solve for the volume contribution ratio of each possible source water sample end member in the leakage water. j = 1, 2, 3…k; k is the number of indicators, n is the number of water sample end elements that may be the source of the leakage, and k ≥ n; In Equation 1: C j It is the value of the j-th index in the seepage water; x i It is the proportion of the volume contribution of the i-th possible source end-member to the leakage water. C ij It is the value of the j-th index in the i-th terminator; Samples from potential water sample endmembers are mixed according to the volume contribution ratios obtained from the above multivariate mixing model to obtain a mixed sample. The anion and cation content and / or trace element content of the mixed sample are measured as simulated values. The variance ratio R between the simulated value and the measured value of the leakage water is calculated according to Equation 2. 2 , denoted as the first coefficient of determination; n is the number of indicators, and its value is the same as k in Formula 1; In Equation 2, x i The measured values ​​of anion, cation, or trace element content in the leaked water, y i These are simulated values ​​for the content of anions, cations, or trace elements in a mixed sample. This represents the average of the measured values ​​of various indicators related to water leakage. (7) Verify the isotopic characteristics of the solution results 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), reconstructing a multivariate mixing model according to step (6), solving for the volume contribution ratio of each possible source water sample endmember, and calculating the second coefficient of determination with reference to step (6). If the absolute value of the difference between the first and second determination coefficients is ≤0.35, it indicates that the volume contribution ratio of each possible source water sample end-member in the leakage water obtained by step (6) is reasonable and passes the verification. Then the first determination coefficient is used as the first qualified determination coefficient. If the absolute value of the difference between the first and second determination coefficients is >0.35, it indicates that the result obtained by step (6) is unreasonable. Replace the possible source water sample end-member and reconstruct the multivariate mixture model according to step (6) until the isotope characteristics are verified and the first qualified determination coefficient is obtained. (8) Based on the water chemical analysis results of step (5), replace the end members of water samples from different possible sources, repeat steps (6) and (7), and obtain a new second qualified determination coefficient verified by isotope characteristics. Compare the first qualified determination coefficient and the second qualified determination coefficient, and take the model result with the higher determination coefficient as the true volume ratio representing the source of leakage water. (9) Based on the actual volume ratio of the seepage source determined in step (8), and combined with the mineralogical composition characteristics obtained in step (4), explore and analyze the path and channel of seepage in the dam body.

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

3. The method for quantitative identification of dam leakage according to claim 1, characterized in that, In step (4), the method for determining the content of anions and cations includes ion chromatography.

4. The method for quantitative identification of dam leakage according to claim 1, characterized in that, In step (4), the method for determining the content of trace elements includes inductively coupled plasma mass spectrometry.

5. The method for quantitative identification of 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 quantitative identification of dam leakage according to claim 1, characterized in that, In step (5), the screening of possible source water sample end-members that are significantly related to the leakage water includes: firstly, preliminarily analyzing the differences and similarities among the distributions of temperature, pH value, total dissolved solids content, anion and cation content, and trace element content of each water sample; secondly, combining the geological background of the dam area, analyzing the hydrochemical characteristics of each water sample; and thirdly, further using correlation analysis and principal component analysis to analyze the correlation between the leakage water and other water samples, and screening possible source water sample end-members that are significantly related to the leakage water.

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

8. The method for quantitative identification of dam leakage according to claim 1, characterized in that, In step (2), the sampling plan is formulated based on the results of the field exploration, including: based on the seepage outflow of the dam observed on the field, a sampling plan is formulated, and sampling is carried out at locations with different water depths and different hydrological characteristics in and around the dam.

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

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