Method for predicting release flux of phosphorus in lake and reservoir bottom mud and application of method

Abstract

The invention belongs to the technical field of water phosphorus pollution, and discloses a method for predicting the release flux of phosphorus in lake and reservoir bottom mud and application of the method. The prediction method comprises the following steps: collecting bottom mud, and obtaining environment variable data and bottom mud phosphorus release amount data of the bottom mud; performing layered sequential screening on the environment variable data of the bottom mud to construct an environment variable-based phosphorus release flux model; coupling the relative abundance of the phosphate solubilizing bacteria with the environment variable group phosphorus release flux model to obtain a model for predicting the phosphorus release flux of the lake and reservoir bottom mud; and inputting the environment variable data and the phosphate solubilizing bacteria relative abundance data of the to-be-detected bottom mud into the model for predicting the phosphorus release flux of the lake and reservoir bottom mud to obtain a bottom mud phosphorus release flux result. The layered sequential screening system is introduced, the equal weight variable hypothesis of a traditional model is broken through, the prediction precision of the model is improved by coupling the relative abundance of the phosphate solubilizing bacteria, and the model is applied to evaluation of the contribution rate of the release flux of the phosphorus in the lake and reservoir sediment to the phosphorus pollution of the water body in the lake and reservoir.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of water body phosphorus pollution, and particularly relates to a method for predicting the phosphorus release flux of lake and reservoir sediment and application thereof. BACKGROUND

[0002] Phosphorus pollution is an important control object in the field of lake and reservoir environmental water quality protection, and its driving effect on water body eutrophication is particularly significant. As a limiting element for the growth of aquatic plants and algae, excessive accumulation of phosphorus can lead to imbalance of primary productivity of water body, and cause a series of ecological problems such as explosive growth of algae and dissolved oxygen depletion. In recent years, with the rapid development of social economy and the continuous increase of environmental governance, the input of exogenous pollution (such as agricultural runoff, domestic sewage and industrial discharge) has been effectively controlled. However, the endogenous phosphorus pollution in lake and reservoir sediment has gradually become prominent, and has become a key factor hindering the further improvement of water quality. The phosphorus in the sediment can be released into the water body under certain environmental conditions, and continuously replenishes the phosphorus concentration in the water body. Therefore, before implementing endogenous governance, it is necessary to determine the flux of sediment phosphorus release and its actual contribution to the phosphorus concentration in the water body, which is not only the premise of scientific governance, but also an important basis for achieving precise management.

[0003] The traditional method for quantitatively evaluating the flux of sediment phosphorus release is usually based on the accumulated content of sediment phosphorus, by analyzing the level of sediment phosphorus content, establishing a data set of sediment phosphorus content, combining with the determination of phosphorus release data set in laboratory simulation experiment, and constructing a prediction model based on the correlation between the two. The core of these methods is to determine the degree of phosphorus release of the sediment by measuring the change of water body phosphorus concentration through adding a certain amount of sediment to the simulated water body, and finally forming an estimation tool for the flux of sediment phosphorus release. However, the traditional method has significant limitations in practical application. On the one hand, existing researches generally use the full variable stacking method, without establishing a variable selection order based on the physical and chemical mechanism of phosphorus release, resulting in high model dimension and ambiguous physical meaning of parameters; on the other hand, microorganisms such as phosphorus solubilizing bacteria have biological driving effect on phosphorus release, and the traditional model lacks quantitative analysis of such biological mechanism. The above technical defects lead to the fact that the traditional model is often difficult to accurately reflect the actual situation when predicting the phosphorus release of complex lake and reservoir sediment, thereby reducing the reliability and applicability of the evaluation results. SUMMARY

[0004] The purpose of the present application is to provide a method for predicting the flux of lake and reservoir sediment phosphorus release, by using a method of hierarchical sequential screening and coupling the relative abundance of phosphorus solubilizing bacteria to establish a model for predicting the flux of lake and reservoir sediment phosphorus release, and applying the model to evaluate the contribution rate of the flux of lake and reservoir sediment phosphorus release to the phosphorus pollution of the water body in the lake and reservoir.

[0005] The purpose of the present application is achieved by the following technical solutions:

[0006] The application provides a method for predicting a lake reservoir sediment phosphorus release flux, comprising the following steps:

[0007] Collecting sediment and obtaining environmental variable data and sediment phosphorus release data of the sediment;

[0008] Performing hierarchical sequential screening on the environmental variable data of the sediment to construct an environmental variable-based phosphorus release flux model;

[0009] Coupling the phosphorus solubilizing bacteria relative abundance and the environmental variable-based phosphorus release flux model to obtain a predicted lake reservoir sediment phosphorus release flux model;

[0010] Inputting the environmental variable data and the phosphorus solubilizing bacteria relative abundance data of the sediment to be tested into the predicted lake reservoir sediment phosphorus release flux model to obtain a sediment phosphorus release flux result;

[0011] In the method, first, the chemical composition of the sediment directly related to the phosphorus release is screened; second, the redox potential and the pH value are sequentially introduced; and finally, the chemical-environmental interaction term, the environmental coupling term and the nonlinear term are directionally introduced.

[0012] In the model construction, after each layer of variable is introduced, the hierarchical regression analysis method is used to verify the model accuracy.

[0013] In some embodiments, the sediment environmental variable data comprises the chemical composition of the sediment and environmental parameters.

[0014] Further, the chemical composition of the sediment comprises the phosphorus content, the iron content and the calcium content of the sediment.

[0015] Further, the environmental parameters comprise the redox potential and the pH value.

[0016] In some embodiments, the environmental variable-based phosphorus release flux model is as follows:

[0017] Y = -1720.90742683621060 + 324.33200888284102 * A + 28.54705860414034 * B - 67.00207565899443 * C + 364.22328225092144 * D + 3.60197696023251 * E - 6.24276701356535 * AB + 17.16803396051859 * AC - 15.91017610246776 * AD - 0.49504472480919 * AE + 0.89029576898247 * BC - 4.15131912624077 * BD - 0.01655518708073 * BE + 4.93864425750997 * CD + 0.09393795922271 * CE - 0.40999975572386 * DE - 27.59541022357863 * A + 0.03178579658933 * B - 0.10155303199914 * C - 16.68006682737522 * D + 0.0000000000000000 * E + 0.0000000000000000 * AB + 0.0000000000000000 * AC + 0.0000000000000000 * AD + 0.0000000000000000 * AE + 0.0000000000000000 * BC + 0.0000000000000000 * BD + 0.0000000000000000 * BE + 0.0000000000000000 * CD + 0.0000000000000000 * CE + 0.0000000000000000 * DE 2 + 0.03178579658933 * B 2 - 0.10155303199914 * C 2 - 16.68006682737522 * D 2

[0018] wherein Y is the phosphorus release flux, the unit of Y is mg / kg / day; A is the phosphorus content of the sediment, the unit of A is mg / g; B is the iron content, the unit of B is mg / g; C is the calcium content, the unit of C is mg / g; D is the pH value; E is the oxidation-reduction potential, the unit of E is mV.

[0019] In some embodiments, the model for predicting the phosphorus release flux of the lake sediment is:

[0020] Y1 = 12.344562 * X + Y

[0021] wherein Y1 is the phosphorus release flux of the lake sediment, the unit of Y1 is mg / kg / day; X is the relative abundance of phosphorus-dissolving bacteria, the unit of X is %; Y is the environmental variable-based phosphorus release flux, the unit of Y is mg / kg / day.

[0022] The application also provides an evaluation method for the contribution rate of the phosphorus release flux of the lake sediment to the phosphorus pollution of the water body in the lake, which is obtained by the method for predicting the phosphorus release flux of the lake sediment as described above, comprising:

[0023] obtaining the increment of the phosphorus concentration of the water body in the lake caused by the phosphorus release flux of the lake sediment;

[0024] obtaining the increment of the phosphorus concentration of the water body in the lake;

[0025] The contribution rate of the sediment phosphorus release flux of the lake or reservoir to the phosphorus pollution of the water body in the lake or reservoir is calculated.

[0026] In some embodiments, the increase in the phosphorus concentration of the water body in the lake or reservoir caused by the sediment phosphorus release flux of the lake or reservoir is obtained in the following manner:

[0027] Δ[P] = Y1 / 1000 × Msed × T / V

[0028] wherein Δ[P] is the increase in the phosphorus concentration of the water body in the lake or reservoir caused by the sediment phosphorus release flux of the lake or reservoir, in mg / L; Msed is the mass of the sediment, in g; T is the time, in day; and V is the volume of the water body, in m 3 .

[0029] In some embodiments, the increase in the phosphorus concentration of the water body in the lake or reservoir is obtained in the following manner:

[0030] d[P] = [Y1 / 1000 × Msed / V + Qin × [P]in / V - Qout × [P] / V] × T

[0031] wherein d[P] is the change in the phosphorus concentration of the water body in the lake or reservoir over time, in mg / L; Qin is the external input flow, in m 3 / day; [P]in is the external input phosphorus concentration, in mg / L; Qout is the output flow, in m 3 / day.

[0032] In some embodiments, the contribution rate of the sediment phosphorus release flux of the lake or reservoir to the phosphorus pollution of the water body in the lake or reservoir is calculated in the following manner:

[0033] Crelease = d[P] / [P]crit

[0034] wherein [P]crit is the critical concentration of phosphorus allowed in the environmental standard, in mg / L;

[0035] When Crelease > 1, it indicates that the internal phosphorus release is a key factor leading to the excessive phosphorus in the water body in the lake or reservoir.

[0036] Compared with the prior art, the present application has the following beneficial technical effects:

[0037] (1) In the model construction stage, the present application innovatively introduces a hierarchical sequential screening system of variables, breaks through the flat variable assumption of traditional models, and realizes the in-depth analysis of the phosphorus release mechanism;

[0038] (2) The contribution of phosphorus solubilizing bacteria to the sediment phosphorus release flux is fully considered, and the prediction accuracy of the model is improved by coupling the relative abundance of phosphorus solubilizing bacteria;

[0039] (3) Put forward a kind of water body phosphorus pollution assessment method based on sediment phosphorus release flux, more comprehensive analysis of the actual influence of endogenous phosphorus release on water body phosphorus pollution. DETAILED DESCRIPTION

[0040] The application will be further described in conjunction with specific embodiments, and the following examples can enable a person skilled in the art to more comprehensively understand the application, but in no way limit the application.

[0041] The application provides a method for predicting lake and reservoir sediment phosphorus release flux, comprising:

[0042] S1, collecting sediment and obtaining sediment environmental variable data and sediment phosphorus release amount data;

[0043] Specifically, the sediment environmental variable data includes sediment chemical composition and environmental parameters; the sediment chemical composition includes sediment phosphorus content, iron content and calcium content; and the environmental parameters include oxidation-reduction potential and pH value.

[0044] The sediment samples at the sampling points were collected by using a rod-holding columnar sediment sampler, and impurities such as gravel, mussels and dry leaves were removed. After standing for 10 minutes, the overlying water was removed, the sediment was loaded into a PE self-sealing bag, the air was exhausted and sealed, and then stored in a 0℃ insulation box. After being brought back to the laboratory, the samples were freeze-dried, stored in a-20℃ refrigerator after processing, and used for subsequent analysis. According to the Ecological Environment Damage Identification and Evaluation Technical Guidelines (GB / T 39792.2-2020), the sediment phosphorus content is determined by alkali fusion-molybdenum antimony spectrophotometry. The iron content is detected by phenanthroline spectrophotometry. The calcium content is detected by atomic absorption spectrophotometry. The oxidation-reduction potential and pH are determined by potential method and electrode method respectively.

[0045] For the phosphorus release flux, first, potassium dihydrogen phosphate is used to prepare a standard phosphorus solution (0.05-0.2mg / L, the specific value is determined according to the total phosphorus content in the overlying water of the target lake and reservoir). Then, according to the water-soil ratio of 90:1 (i.e. 45mL:0.5g), the system is configured (i.e. the above-mentioned sediment sample and phosphorus-containing acid solution are mixed), and after being shaken at 25℃ for 24h, it is separated by centrifugation (speed of 10000rpm, time of 10 minutes). Then, the supernatant is treated by 0.45μm fiber filter membrane, and the concentration of total phosphorus in the solution is determined according to the standard method "Determination of Total Phosphorus in Water and Wastewater-Ammonium Molybdate Spectrophotometric Method (GB 11893-89)" in "Water and Wastewater Monitoring and Analysis Methods (4th Edition)", and then the phosphorus release flux is calculated based on the following formula.

[0046] Phosphorus release flux = ((C-C0)×V) / m / T

[0047] Wherein, C is the concentration of phosphorus in overlying water after treatment (mg / L), C0 is the concentration of phosphorus in the initial standard phosphorus solution (mg / L), V is the volume of the standard phosphorus solution added to the system (L), m is the mass of the treated sediment (kg), and T is the treatment duration (day)

[0048] It should be noted that the application is applicable to lakes and reservoirs that meet the V-class surface water standard in the Chinese Surface Water Environmental Quality Standard, i.e., the total phosphorus content in the water should be less than or equal to 0.2 mg / L.

[0049] S2, layering and sequentially screening the environmental variable data of the sediment to construct an environmental variable-based phosphorus release flux model;

[0050] Specifically, the method of layering and sequential screening is as follows: first, screening the chemical composition of the sediment directly related to phosphorus release; second, sequentially introducing the oxidation-reduction potential and pH value; and finally, introducing the chemical-environmental interaction term, the environmental coupling term, and the nonlinear term in a targeted manner; in the model construction, after each layer of variables is included, hierarchical regression analysis is used to verify the accuracy of the model.

[0051] It should be noted that the specific method of hierarchical sequential screening is: preferentially screening the chemical form variable directly related to phosphorus release, taking the total phosphorus content of the sediment (A) as the core basis of release potential; and through correlation analysis, considering the substance in the sediment storage content and the phosphorus binding form, it is clear that the iron content (B) and calcium content (C) are the key carriers of combined phosphorus (Fe-P, Ca-P), and the lanthanum element and aluminum element with high combined state of phosphorus are eliminated from the system index because of their low content in the sediment and cannot form an advantage in absolute quantity; and then determine the total phosphorus content, iron content and calcium content of the sediment as the key material basis affecting the phosphorus release flux. Then, according to the response time difference of environmental parameters to the release process, according to the classification characteristics of fast variables and slow variables, the oxidation-reduction potential (E) and pH value (D) are introduced in sequence, the former is defined as a fast variable, and its change lags behind the release flux by 4-6 hours (the research results show that when the oxidation-reduction potential in the sediment environment of the lake and reservoir changes, the phosphorus release flux will not change immediately, but will change after 4-6 hours), directly controlling the dissolution of iron and manganese oxides (such as low oxidation-reduction potential triggering Fe-P release); the latter is a slow variable, because the variable adjusts the surface charge of the sediment and the chemical equilibrium of phosphorus (such as alkaline promoting Ca-P dissolution), lags behind the release flux by 2-3 hours (the research results show that the phosphorus release flux changes first, and the pH value changes 2-3 hours later), based on the above considerations, the control process is decomposed when the model is constructed. Finally, for the nonlinear mechanism in complex environment, through the ridge regression regularization test, the chemical-environmental interaction term (such as AB, AD), the environmental coupling term (such as CD, DE) and the nonlinear term (such as A 2 、D 2 ) are introduced, the threshold value of phosphorus release is identified, and the mechanism affecting the release of phosphorus is deepened, and the synergistic effect between different factors is considered.

[0052] It should be noted that in the model construction, after each layer variable is included, hierarchical regression analysis is used to verify the model explanation increment (ΔR 2 ) and joint significance (p<0.01), to ensure that the variable selection conforms to the physical and chemical path of phosphorus release, and to avoid the disorderly variable stacking of traditional models. Specifically, after each layer variable is included, the hierarchical regression analysis is verified in the following way: calculate the explanation increment (ΔR 2 ) of the current layer model relative to the previous layer model, which reflects the contribution of the newly included variable group to the explanation of the variation of the sediment phosphorus release amount. When a layer variable is included, if ΔR 2 reaches a significant level, it indicates that the layer variable contains effective information related to phosphorus release and should be retained in the model, and if ΔR 2Approaching zero or no practical significance, it shows that the layer variable has no significant contribution to the model explanation power, and can be considered to be removed; Joint significance test (p-value test) is performed to verify whether the regression coefficients of the newly added variable group are overall significantly not zero (set the significance level to p<0.01), and the joint significance of the newly added variable group is judged by F test, when p<0.01, it indicates that there is a statistically significant correlation between the layer variable and the release amount of sediment phosphorus, and it is in line with the physical and chemical path of phosphorus release.

[0053] Therefore, the environmental variable-based phosphorus release flux model provided by the application is:

[0054] Y=-1720.90742683621060+324.33200888284102×A+28.54705860414034×B-67.00207565899443×C+364.22328225092144×D+3.60197696023251×E-6.24276701356535×AB+17.16803396051859×AC-15.91017610246776×AD-0.49504472480919×AE+0.89029576898247×BC-4.15131912624077×BD-0.01655518708073×BE+4.93864425750997×CD+0.09393795922271×CE-0.40999975572386×DE-27.59541022357863×A 2 +0.03178579658933×B 2 -0.10155303199914×C 2 -16.68006682737522×D 2

[0055] Wherein, Y is the phosphorus release flux, the unit of Y is mg / kg / day; A is the phosphorus content of the sediment, the unit of A is mg / g; B is the iron content, the unit of B is mg / g; C is the calcium content, the unit of C is mg / g; D is the pH value; E is the oxidation-reduction potential, the unit of E is mV.

[0056] S3, the relative abundance of phosphorus solubilizing bacteria is coupled with the environmental variable-based phosphorus release flux model to obtain a predicted lake and reservoir sediment phosphorus release flux model;

[0057] Specifically, the predicted lake and reservoir sediment phosphorus release flux model is:

[0058] Y1=12.344562×X+Y

[0059] wherein Y1 is the phosphorus release flux of lake sediment, in mg / kg / day; X is the relative abundance of phosphorus solubilizing bacteria, in %; Y is the environmental variable base phosphorus release flux, in mg / kg / day;

[0060] The enrichment characteristics of the phosphorus solubilizing bacteria in the sediment can be obtained by 16S amplicon sequencing technology or metagenomic sequencing technology, and then the relative abundance value can be obtained by the ratio of the number of OTUs of the phosphorus solubilizing bacteria to the number of total bacterial OTUs.

[0061] It should be noted that the phosphorus solubilizing bacteria is a kind of microorganism that can convert insoluble phosphorus compounds into soluble phosphate, and its activity can cause the fixed phosphorus in the sediment to be released again, thereby enhancing the release of phosphorus in the sediment. The research team found that when the relative abundance of the typical phosphorus solubilizing bacteria-Bacillus (Bacillus as a typical phosphorus solubilizing bacteria, in the sediment environment, can decompose and convert insoluble organic phosphorus and inorganic phosphorus compounds in the sediment into soluble phosphorus through the secretion of acidic substances and phosphatase, thereby aggravating the phosphorus pollution in the water body) is greater than 1% or more, there is a significant linear relationship between the relative abundance of the bacteria and the release of phosphorus as described above. When the relative abundance of the phosphorus solubilizing bacteria is not greater than 1%, the influence of the phosphorus solubilizing bacteria on the release of phosphorus is small, and X is 0. The phosphorus solubilizing bacteria described in the present application are preferably Bacillus, which is a typical phosphorus solubilizing bacteria.

[0062] The environmental variable data and the relative abundance data of the phosphorus solubilizing bacteria of the sediment to be tested are input into the prediction model of the phosphorus release flux of the lake sediment, and the phosphorus release flux of the sediment is obtained.

[0063] Specifically, the measured phosphorus content, iron content, calcium content, pH value, oxidation-reduction potential and relative abundance of the phosphorus solubilizing bacteria of the sediment are substituted into the prediction model of the phosphorus release flux of the lake sediment, and the phosphorus release flux of the sediment is obtained.

[0064] In the lake ecosystem, the release of endogenous phosphorus has a significant influence on the phosphorus concentration in the water body, but its importance is restricted by various factors, such as the volume of the water body, the background phosphorus concentration and the external phosphorus input. In order to more comprehensively analyze the actual influence of the release of endogenous phosphorus, the present application further provides an evaluation method for the contribution rate of the phosphorus release flux of the lake sediment to the phosphorus pollution in the water body in the lake, which is obtained based on the prediction method of the phosphorus release flux of the lake sediment as described above, comprising:

[0065] S1, obtaining the increment of the phosphorus concentration in the water body in the lake caused by the phosphorus release flux of the lake sediment;

[0066] Specifically, the way to obtain the increment of the phosphorus concentration in the water body in the lake caused by the phosphorus release flux of the lake sediment is:

[0067] Δ[P] = Y1 / 1000 x Msed x T / V

[0068] wherein Δ[P] is the increment of phosphorus concentration in the water body caused by the phosphorus release flux of the lake and reservoir sediment, with the unit of mg / L; Msed is the mass of the sediment, with the unit of g; T is the time, with the unit of day; and V is the volume of the water body, with the unit of m 3 .

[0069] The mass of the sediment Msed can be calculated by collecting sediment samples at multiple points in the lake and reservoir, measuring the volume and density of the samples, and then calculating the total mass; the time T is determined according to the research period or monitoring period; and the volume of the water body V can be estimated by using the integral method or empirical formula based on the topographic map of the lake and reservoir and the water depth measurement data.

[0070] S2, obtaining the increment of phosphorus concentration in the water body in the lake and reservoir;

[0071] Specifically, the way to obtain the increment of phosphorus concentration in the water body in the lake and reservoir is:

[0072] d[P] = [Y1 / 1000 x Msed / V + Qin x [P]in / V - Qout x [P] / V] x T

[0073] wherein d[P] is the change of phosphorus concentration in the water body in the lake and reservoir with time, with the unit of mg / L; Qin is the external input flow, with the unit of m 3 / day; [P]in is the external input phosphorus concentration, with the unit of mg / L; and Qout is the output flow, with the unit of m 3 / day.

[0074] The phosphorus concentration [P] in the water body in the lake and reservoir is determined by regularly collecting water samples at different points and different water layers and using chemical analysis methods such as molybdenum-antimony anti-spectrophotometry; the external input flow Qin and the output flow Qout can be measured by installing flowmeters at the inflow and outflow, or obtained through hydrological monitoring data; and the external input phosphorus concentration [P]in is determined by collecting water samples at each external input port and using the same chemical analysis method as [P].

[0075] S3, calculating the contribution rate of the phosphorus release flux of the lake and reservoir sediment to the phosphorus pollution in the water body in the lake and reservoir.

[0076] Specifically, the way to calculate the contribution rate of the phosphorus release flux of the lake and reservoir sediment to the phosphorus pollution in the water body in the lake and reservoir is:

[0077] Crelease = d[P] / [P]crit

[0078] wherein [P]crit is the critical concentration of phosphorus allowed in the “Environmental Quality Standards for Surface Water in China”, with the unit of mg / L;

[0079] When Crelease>1, it indicates that endogenous phosphorus release is the key factor leading to excessive phosphorus in the water body of the lake and reservoir.

[0080] Comparative Example 1:

[0081] Compared with the example, the model obtained in Comparative Example 1 is not coupled with the relative abundance of phosphorus-releasing bacteria, that is, the model in Comparative Example 1 is the environmental variable base phosphorus release flux model in the above example, and other conditions are consistent. The model reaches a significant test level (P<0.05) and has statistical significance, and can be used for data prediction.

[0082] Comparative Example 2:

[0083] Compared with the example, Comparative Example 2 only considers the phosphorus content (A) and calcium and iron contents (B and C) in the sediment as parameters to obtain the model, and other conditions are consistent. The obtained model is:

[0084] Y=-16.59497560140032+367.04633600875945xA-5.23159048421255xB+8.64196936231641xC-6.62256451747886xAxB+9.46110278508099xAxC-0.20144292975914xBxC-90.45966745235243xA 2 +0.13880478418358xB 2 -0.08665741552906xC 2

[0085] wherein Y is the phosphorus release flux of the lake and reservoir sediment, unit: mg / kg / day; A is the phosphorus content of the sediment, unit: mg / g; B is the iron content, unit: mg / g; and C is the calcium content, unit: mg / g.

[0086] The model reaches a significant test level (P<0.05) and has statistical significance, and can be used for data prediction.

[0087] Comparative Example 3:

[0088] Compared with the example, Comparative Example 3 only considers the phosphorus content (A) in the sediment as a parameter to obtain the model, and other conditions are consistent.

[0089] The obtained model is:

[0090] Y=-25.24738795284777+205.44656055111378xA-103.99232390362775xA 2

[0091] Wherein, Y is the lake and reservoir sediment phosphorus release flux, unit is mg / kg / day; A is the sediment phosphorus content, unit is mg / g.

[0092] The model reaches the significance test level (P<0.05), and has statistical significance, and can be used for data prediction.

[0093] Comparative Example 4:

[0094] Compared with Comparative Example 1, Comparative Example 4 adds the sediment lanthanum content (F), the sediment aluminum content (G) and the dissolved oxygen content (T) as parameters, and adopts the variable stacking mode to construct the model.

[0095] The obtained model is:

[0096] Y=387.688+90.084*A-4.506*B+7.782*C--87.608*D+0.122*E+479.788*F+90.268*G+6.244*T-40.703*A 2 +0.075*B 2 +5.555*D 2 -13626.058*F 2 -122.063*G 2 -1.702*T 2

[0097] Wherein, Y is the lake and reservoir sediment phosphorus release flux, unit is mg / kg / day; A is the sediment phosphorus content, unit is mg / g; B is the iron content, unit is mg / g; C is the calcium content, unit is mg / g; D is the pH value; E is the oxidation-reduction potential, unit is mV; F is the sediment lanthanum content, unit is mg / g; G is the sediment aluminum content, unit is mg / g; T is the dissolved oxygen content, unit is mg / L.

[0098] The model reaches the significance test level (P<0.05), and has statistical significance, and can be used for data prediction.

[0099] The model prediction results of the embodiment of the application are compared with Comparative Examples 2 and 3, and the results are shown in Table 1, the prediction value of the prediction model constructed by the application is closer to the actual determination situation, and the prediction accuracy of the models constructed by Comparative Examples 2 and 3 is significantly reduced, and in particular, the prediction accuracy of Comparative Example 3 is generally the lowest because only the phosphorus content in the sediment is considered in the model construction process.

[0100] The model established in the embodiment of the present application is compared with Comparative Example 1, and the prediction results are shown in Table 1 as Sample 3 and Sample 5. When the relative abundance of phosphorus solubilizing bacteria is greater than 1%, the prediction result of the model coupled with the relative abundance of phosphorus solubilizing bacteria is closer to the actual measured phosphorus release flux than the model without coupling the relative abundance of phosphorus solubilizing bacteria, indicating that coupling the relative abundance of phosphorus solubilizing bacteria can improve the prediction accuracy of the model. Moreover, the prediction results of the model coupled with the relative abundance of phosphorus solubilizing bacteria (67.10 mg / kg / day for Sample 3 and 14.41 mg / kg / day for Sample 5) are both greater than the prediction results of the model without coupling the relative abundance of phosphorus solubilizing bacteria (66.82 mg / kg / day for Sample 3 and 13.97 mg / kg / day for Sample 5), proving the importance of phosphorus solubilizing bacteria for phosphorus release.

[0101] Table 1 Comparison of prediction results of different models

[0102]

[0103]

[0104] In addition, the model constructed in the present application is significantly better than the traditional full-variable stacking method in terms of prediction accuracy of phosphorus release flux. The model constructed in the present application achieves more stable and accurate prediction results with fewer variables, especially in complex sediment environments, the prediction difference is reduced by 60%-70% compared with the traditional method, which has strong reliability. Specifically, the prediction difference (prediction difference calculation method: | (actual phosphorus release flux-predicted phosphorus release flux) | / actual phosphorus release flux x 100%) of the model (Comparative Example 1) constructed by the present application by screening five core variables of sediment phosphorus content, iron content, calcium content, pH value and oxidation-reduction potential for five samples is 0.10%, 1.27%, 5.02%, 37.61% and 30.60% respectively; the prediction difference (prediction difference calculation method: | (actual phosphorus release flux-predicted phosphorus release flux) | / actual phosphorus release flux x 100%) of the model (embodiment) constructed by coupling the relative abundance of phosphorus solubilizing bacteria for Sample 3 and Sample 5 is reduced to 4.62% and 28.42% respectively, so overall, the model constructed in the present application has high consistency between the overall prediction result and the actual value; while the traditional method (Comparative Example 4) significantly deviates from the true value due to the addition of redundant variables such as dissolved oxygen, lanthanum content and aluminum content (although these variables theoretically have an impact on the transfer of phosphorus in sediment), indicating that the full-variable stacking method has a significant decrease in prediction accuracy due to interference between variables. Moreover, the model constructed by adding parameters such as water transparency, chlorophyll content and sediment copper content according to the traditional method will also have a significant decrease in prediction accuracy due to interference between variables.

[0105] Although the embodiments of the present application have been shown and described above, it is understood that the above-described embodiments are exemplary and are not to be construed as limiting the present application, and that changes, modifications, substitutions and variations can be made by those skilled in the art without departing from the spirit and scope of the present application.

Claims

1. A method for predicting the phosphorus release flux from the sediment of a lake or reservoir, characterized in that, The method comprises the following steps: collecting sediment and obtaining environmental variable data and phosphorus release data of the sediment; performing hierarchical sequential screening on the environmental variable data of the sediment to construct an environmental variable-based phosphorus release flux model; coupling the relative abundance of phosphorus solubilizing bacteria and the environmental variable-based phosphorus release flux model to obtain a predicted lake sediment phosphorus release flux model; inputting the environmental variable data and the relative abundance data of the phosphorus solubilizing bacteria of the sediment to be tested into the predicted lake sediment phosphorus release flux model to obtain a sediment phosphorus release flux result; wherein the hierarchical sequential screening method comprises the following steps: firstly, screening the chemical composition of the sediment which is directly related to phosphorus release; secondly, sequentially introducing the oxidation-reduction potential and the pH value; and finally, introducing the chemical-environmental interaction term, the environmental coupling term and the nonlinear term in a targeted manner; in the model construction, after each layer of variables is introduced, hierarchical regression analysis is used to verify the accuracy of the model.

2. The method of predicting the sediment phosphorus release flux of a lake reservoir according to claim 1, characterized in that, The sediment environmental variable data comprises sediment chemical composition and environmental parameters.

3. The method of predicting the sediment phosphorus release flux of a lake reservoir according to claim 2, characterized in that, The sediment chemical composition comprises phosphorus content, iron content and calcium content of the sediment.

4. The method of claim 2, wherein, The environmental parameters comprise oxidation-reduction potential and pH value.

5. The method of predicting the sediment phosphorus release flux of a lake reservoir according to claim 1, characterized in that, The environmental variable-based phosphorus release flux model is as follows: Y = -1720.90742683621060 + 324.33200888284102 * A + 28.54705860414034 * B - 67.00207565899443 * C + 364.22328225092144 * D + 3.60197696023251 * E - 6.24276701356535 * AB + 17.16803396051859 * AC - 15.91017610246776 * AD - 0.49504472480919 * AE + 0.89029576898247 * BC - 4.15131912624077 * BD - 0.01655518708073 * BE + 4.93864425750997 * CD + 0.09393795922271 * CE - 0.40999975572386 * DE - 27.59541022357863 * A 2 + 0.03178579658933 * B 2 - 0.10155303199914 * C 2 - 16.68006682737522 * D 2 wherein Y is the phosphorus release flux, the unit of Y is mg / kg / day; A is the phosphorus content of the sediment, the unit of A is mg / g; B is the iron content, the unit of B is mg / g; C is the calcium content, the unit of C is mg / g; D is the pH value; and E is the oxidation-reduction potential, the unit of E is mV.

6. The method of predicting the sediment phosphorus release flux of a lake reservoir according to claim 1, characterized in that, The predicted lake sediment phosphorus release flux model is as follows: Y1=12.344562×X+Y wherein Y1 is the lake sediment phosphorus release flux, the unit is mg / kg / day; X is the relative abundance of phosphorus solubilizing bacteria, the unit is %; and Y is the environmental variable-based phosphorus release flux, the unit is mg / kg / day.

7. A method for evaluating the contribution rate of the phosphorus release flux of lake and reservoir sediment to the phosphorus pollution of water in the lake and reservoir, characterized in that, The method comprises the following steps: obtaining the increment of the water body phosphorus concentration in the lake caused by the lake sediment phosphorus release flux; obtaining the increment of the water body phosphorus concentration in the lake; calculating the contribution rate of the lake sediment phosphorus release flux to the water body phosphorus pollution in the lake; the lake sediment phosphorus release flux is obtained by the method for predicting the lake sediment phosphorus release flux according to any one of claims 1-6.

8. The evaluation method according to claim 7, wherein the method for obtaining the increment of the water body phosphorus concentration in the lake caused by the lake sediment phosphorus release flux is as follows: Δ[P]=Y1 / 1000×Msed×T / V wherein Δ[P] is the increment of the water body phosphorus concentration in the lake caused by the lake sediment phosphorus release flux, the unit is mg / L; and Msed is the mass of the sediment, the unit is g. T is time in day; V is the volume of the water body in m 3 .

9. The evaluation method according to claim 7, wherein the method for obtaining the increment of the water body phosphorus concentration in the lake is as follows: d[P]=[Y1 / 1000×Msed / V+Qin×[P]in / V-Qout×[P] / V]×T where d[P] is the change of phosphorus concentration in the water body in the lake or reservoir over time, in mg / L; Qin is the exogenous input flow, in m 3 / day; [P]in is the exogenous input phosphorus concentration, in mg / L; Qout is the output flow, in m 3 / day.

10. The evaluation method according to claim 7, characterized in that the method for calculating the contribution rate of the lake sediment phosphorus release flux to the water body phosphorus pollution in the lake is as follows: Crelease=d[P] / [P]crit wherein [P]crit is the critical concentration of phosphorus allowed in the environmental standard, the unit is mg / L. When Crelease > 1, it means that the endogenous phosphorus release is the key factor leading to the excessive phosphorus in the water body of the lake and reservoir.

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