Coal Mine Water Research Articles

Comprehensive Water Inrush Risk Assessment Method for Coal Seam Roof

In order to prevent coal mine water inrush accidents, it is necessary to appropriately assess the water abundance of coal mines based on drilling and geophysical data. This paper studied a comprehensive risk assessment method of water inrush. First, a water inrush risk index was proposed based on the analytic hierarchy process-entropy method (AHP-EM) and the water-rich structure index was proposed based on the geological data coupled calculation, then weighted two indices above which established the comprehensive water inrush risk assessment method. Secondly, eight factors were chosen as risk control factors of water inrush: core recovery, aquifer thickness, distance from the indirect aquifer to the coal seam, aquiclude thickness, height of water-conducting fracture zone, sand-mud ratio, total layers of aquifer and aquiclude, and the equivalent thickness of sandstone. Finally, the No. 2 coal seam of Dahaize coal mine was taken as the research object, the factors were calculated, and a comprehensive water inrush assessment model was constructed. With site investigation and observation, the water inrush risk assessment model of the No.2 coal seam roof is consistent with the actual mining situation, which verifies the validity of the model. In addition, this method was used to evaluate the water-richness of the weathered bedrock fractured aquifer in the Zhangjiamao coal mine. The practical application of the two mines has verified the generality of the approach. The research could provide scientific assistance for mine water hazard mitigation and mining safety.

Quantitative Inversion Model Design of Mine Water Characteristic Ions Based on Hyperspectral Technology

In view of the problems of low measurement accuracy and repeated calibration during the use of coal mine water quality analysis, the hyperspectral reflection noncontact measurement technology was proposed to solve the existing problems. KCl, NaCl, pH, NaHCO3, and CaCl2were used to indicate the characteristic ion information of Na+, K+, Ca2+, Cl−, HCO3−, and pH mine water in the laboratory, and 2220 spectral data were obtained by spectral determination. Savitzky–Golay convolution smoothing was used to smooth and denoise the original spectral data of each ion, and the relationship between the spectrum and the concentration of each reagent was obvious after smoothing and denoising pretreatment. The principal component regression method was used to build the inversion model of each ion content, and through the modeling study, the prediction set of KCl was found: the coefficient R∧2 reaches 0.907, RPD is up to 2.7; the prediction set of NaCl was found: the coefficient R∧2 reaches 0.957, RPD is up to 3.1; the PH prediction set was found: the coefficient R∧2 reaches 0.785, RPD is up to 2.1; the prediction set of NaHCO3 was found: the coefficient R∧2 reaches 0.137, RPD is up to 1.2; the prediction set of CaCl2 was found: the coefficient R∧2 reaches 0.622, and RPD is up to 1.7. The results show that the hyperspectral method can play a better role in the extraction of K+, Cl−, Na+, Ca2+, and pH. It is difficult to extract HCO3− ions.

Allocation and Utilization of Coal Mine Water for Ecological Protection of Lakes in Semi-Arid Area of China

In the background of water ecological protection, how to utilize the superfluous coal mine water efficiently has become an urgent problem, especially in northwest China, where the fragile ecological environment needs to be protected but lacks water. To solve this problem, this study proposes a new procedure for the allocation and utilization of mine water aimed at the ecological protection of lakes in an arid and semi-arid area. Based on the water balance method, the ecological water supplement of regional lakes is first estimated according to their different protection goals. Next, a trend analysis of water demand and supply is carried out, and the mine water inflow and available quantity are calculated. Meanwhile, the water resource allocation plan is evaluated systematically. In this study, the procedure is applied to the mine water and lakes in Wushen Banner, Inner Mongolia Autonomous Region of China. The results show that: (1) the lakes can be divided into three classifications according to their ecological protection goals, (2) the available amount of mine water will reach 57.17–81.97 million m3 in 2030, and there are about 46.7 million m3 of water that can be adjusted to reach the optimal utilization in 2020, and (3) the mine water after advanced treatment could meet the requirement of lakes. Finally, it outputs the water supplement path and the water quantity, as well as the water transmission pipelines to each lake, which makes up a new water resources allocation plan and a utilization mode of regional mine water. This utilization mode can provide solutions and ideas for improving the ecological environment of regional lakes and promote the construction of regional ecological safety barriers. Moreover, it can be very helpful for optimizing the allocation of regional water resources, and for improving the reasonable utilization of coal mine water.

Review and Challenges in the Geophysical Mapping of Coal Mine Water Structure

Generally, the water-bearing structures of coal mines mainly include coal seam, roof, coal seam, floor, and goaf, while the main water-conducting structures include faults, collapsed columns, and collapsed goaf areas. The most commonly used methods for the detection of the above structures include the seismic method, high-density electrical method, controlled source audio-frequency magnetotelluric method, and transient electromagnetic method. Theoretically, the seismic methods have a higher resolution, which can be used to determine the targets’ geometry, but unable to determine whether the target is filled with water, while the electromagnetic methods are capable of this, although with lower resolution. Therefore, it is necessary to adopt the comprehensive geophysical prospecting in the actual field measurement of the coal mine water to guarantee the detection accuracy. Based on this, in the passage, first, we introduced the characteristics of the water-bearing and water-conducting structures and then analyzed the detection results of different methods by examples. Finally, we pointed out that, first, it is essential to develop the mine or airborne methods for the sake of convenience; and second, it is time that we adopt three-dimensional detection technology, multisource and multiresolution detection technology, and electromagnetic big data technology for high accuracy.

Research on Multi-Level Scheduling of Mine Water Reuse Based on Improved Whale Optimization Algorithm

Aiming at the problem of the inefficiency of coal mine water reuse, a multi-level scheduling method for mine water reuse based on an improved whale optimization algorithm is proposed. Firstly, the optimization objects of mine water reuse time and reuse cost are used to establish the optimal scheduling model of mine water. Secondly, in order to overcome the defect that the whale optimization algorithm (WOA) is prone to local convergence, the opposition-based learning strategy is introduced to speed up the convergence speed, the Levy flight strategy is used to enhance the ability of the algorithm to jump out of the local optimization, the nonlinear convergence factor is used to balance the global and local search ability, and the adaptive inertia weight is used to improve the optimization accuracy of the algorithm. Finally, the improved whale optimization algorithm (IWOA) is applied to the mine water optimization scheduling model with multiple objects and constraints. The results show that the reuse efficiency of the multi-level scheduling method of mine water reuse is increased by 30.2% and 31.9%, respectively, in the heating and nonheating seasons, which can significantly improve the reuse efficiency of mine water and realize the efficient utilization of mine water reuse deployment. At the same time, experiments show that the improved whale optimization algorithm has higher convergence accuracy and speed, which proves the feasibility and superiority of its improvement strategies.

Identification of Mine Mixed Water Inrush Source Based on Genetic Algorithm and XGBoost Algorithm: A Case Study of Huangyuchuan Mine

Mine water inrush disaster seriously threatens the production of coal mine. Rapid and accurate identification of mine water inrush sources is a key premise for mine water disaster prevention. The conventional research on the identification of water inrush source has focused on a single source, and the identification of mixed water samples from multi-source aquifers in deep coal mining environment is not yet fully explored. In this study, absorption spectrum technology was introduced into the identification of water inrush sources. The absorption spectra of the water samples with different mixing ratios were prepared using the ultraviolet and visible spectrophotometry (UV–Vis) spectrophotometer. In addition, spectral data preprocessing such as scattering correction, baseline correction, smoothing and denoising, and data enhancement were conducted to reduce the influence of experimental error, environment, radiation, molecular interaction, and other factors on the spectral data. Furthermore, a genetic algorithm (GA) was used to improve the seven parameters of the extreme gradient boosting (XGBoost) algorithm, such as learning rate, base model selection, tree parameters, regularization parameters, and iteration times. The deep-learning classifier of mine mixed water sources based on GA-XGBoost was established and used to identify 66 groups of mixed water sources in the Huangyuchuan Mine. The simulation results show that spectral preprocessing and normalization enhancement effectively improved the accuracy of the discriminant model. After 100 cross-validations, the average recognition accuracy of the GA-XGBoost model was 94%, and the results were accurate and reliable. This study provides a new direction and method for the identification of water inrush sources, particularly for mixed water inrush sources. It may also serve as a technical reference for decision-makers to formulate effective coal mine water inrush prevention and control programs and for mine water disaster prevention in similar coalfields in North China.

Theoretical and experimental evaluation of water injection difficulty based on coal structure characteristics

In order to solve the problem of lack of accurate judgment criteria for coal seam water injection difficulty, in this study, the seepage model is coupled with the mathematical evaluation method by using the Morris screening method and the set pair theory, the relationship between the optimal criterion connection degree and each main control factor is established through the multiple linear regression analysis method, and the evaluation index system of water injection difficulty is developed. Furthermore, the relationships between the evaluation index P and each main controlling factor are explored, and the validity of the evaluation index system is verified by comparing with the corresponding experimental results. Through analysis and discussion, the following conclusions are drawn: (1) Coal seams are classified into four categories according their capacity of water injection, i.e., non-water-injectable coal seam for the evaluation index value P ∈ [0, 0.25), difficult water-injection coal seam for [0.25, 0.5), relatively easy water-injection coal seam for [0.5, 0.75), and easy water-injection coal seam for [0.75, 1]. (2) At different parameter values, with the increase of the firmness coefficient, tortuosity fractal dimension, and volume fractal dimension, there are 6, 1, and 1 turning points where the water injection interval changes. The evaluation index value increases with the increase of the effective porosity, and it is stable in the difficult water-injection interval or the easy water-injection interval. (3) Coal Sample X1 and X2 belong to relatively easy water-injection coal seams, and Coal Sample X3, X4, and X5 belong to difficult water-injection coal seams. The five coal samples in the order of water injection difficulty from low to high are: X2 > X1 > X5 > X4 > X3. These findings have theoretical guiding significance for coal mine water injection engineering.

Risk Assessment of Water Inrush of a Coal Seam Floor Based on the Combined Empowerment Method

With the exploitation of the lower coal seams of the Taiyuan Formation, the Ordovician limestone water inrush in the floor became more serious. This paper considers the 162 and 163 mining areas of the Jiangzhuang Coal Mine, in Shandong Province, China. A comprehensive analysis of the geological and hydrogeological conditions of the mining area revealed the following: water pressure and water richness provide the water source and power for the floor water inrush; the thickness of the effective aquifer and the ratio of brittle rock can restrain floor water inrush; fault structures provide water inrush channels; and mining damage is an artificial interference and increases the probability of water inrush. Therefore, six factors: the water pressure of the Ordovician limestone aquifer, water abundance of the Ordovician limestone aquifer, equivalent thickness of effective aquifuge, brittle rock ratio, fracture structure, and mining destruction were selected as the influencing factors on water penetration of the bottom plate, and drawing software was used to establish a mining area map of related factors. The improved fuzzy hierarchical analysis method is more suitable for analyzing multi-objective decisions than the traditional hierarchical analysis method, but the weighting of results is influenced by expert experience. The entropy weight method is data-driven, and the empowerment results are objective. The improved fuzzy analytic hierarchy process and entropy weight method were coupled together, to determine the weight of each factor. The new method is not only data driven, but also takes empirical experience into consideration, making the empowerment results more reasonable. An evaluation of coal floor water inrush was established using MapGIS10.6, which is a general tool-type geographic information system software developed by the China University of Geosciences; and the risk of Ordovician limestone water inrush in the floor of the study area was classified into four levels: dangerous, relatively dangerous, relatively safe, and safe. The whole evaluation process is simple, but the evaluation results have practical importance and are very efficient, providing theoretical support for coal mine water prevention and control engineering.

Hydrogeochemical vertical zonation and evolution model of the Kongjiagou coalmine in Sichuan, China

Abstract With mine drainage and activities, the hydrogeochemical environments has greatly changed in Kongjiagou coalmine, Sichuan Province, southwest China. This study aimed to summarize an ideal model of coalmine hydrogeochemical zonation and evolution. In total, 24 groundwater samples from different depth were collected to analyze their components, with the combination of methods such as ion sources, normalization index, ions ratios, cation exchange and inverse modeling. The hydrogeochemical formation main factor was water–rock reactions and more weathering by sulfuric acid. Dissolution and pyrite oxidation were the main sources of , whereas carbonate weathering was the dominant source of . The vertical extent could be distinguished to three zones by mean and standard deviation of burial depth. The normalization index, ions ratios, cation exchange and water types exhibited clear vertical zonation. In shallow groundwater, dissolution led to a Ca- type water and overall stable concentrations of ions. Redox reactions in the middle region have caused significant increases in the total dissolved solids (TDS) and and a considerable reduction in pH; hence, Ca + Mg-SO4 + HCO3 became the dominant type. Re-dissolution and cation exchange played important roles at depth and caused the pH and TDS to increase slowly. The , Ca2+, and Mg2+ concentrations increased rapidly, whereas the concentration remained basically unchanged, and the water type was either Ca + Mg-HCO3 + SO4 or Na-HCO3 + SO4. This study will be of great significance to coalmine safety production and water environments protection.

Advantages of liming combined to Sedimentation-Dredging in reducing heavy metals and metalloid in water from a coal mining area

A study on the advantages of liming combined to sedimentation-dredging to reduce heavy metals and metalloid in coal mining water was performed in tailing wastewater sedimentation ponds, mixed water sedimentation ponds, and Sangatta River where water from the coal mining area flows in. The concentrations of heavy metals and metalloid showed that the results were not significantly different (P > 0.05) between water from ponds or reservoirs of coal mining and water in the Sangatta River. The liming combined to sedimentation and the followed regular dredging of the sediment was useful in reducing the metals and metalloid in water from the coal mining area before being released into the public water.

Analysis on the Importance of Coal Mine Water Prevention and Hydrogeological Work

Analysis on the Importance of Coal Mine Water Prevention and Hydrogeological Work

Study on Hydraulic Connection and Seepage Law of Goaf Groups in Coal Mine Underground Reservoir

A coal mine underground reservoir, composed of a large number of goaf groups, is effective in achieving the protective utilization of coal mine water. Mastering the hydraulic connection between the goaf groups and the law of seepage is the key to the design and safe operation of coal mine underground reservoirs. Coal/rock sample seepage tests were conducted in Wanli No. 1 Mine in the Shendong mining area according to the evolution law of the lateral supporting pressure of the coal pillars. From the tests, the function of vertical stress in relation to the permeability of coal/rock samples was obtained and the distribution law of permeability of porous media in the goaf was revealed. On this basis, the computational fluid dynamics (CFD) numerical calculation of seepage properties of the coal/rock pillars was conducted. The results show that with the decrease of water level in the goaf and the increase of coal pillar width, the flow range and flow velocity keep decreasing. At the water level of 18.65, 28.65, and 38.65 m, the critical coal pillar widths for the goaf water to penetrate into the adjacent goaf are 30, 50, and 70 m, respectively. When the coal pillar width is less than 10 m, the water can bypass the elastic core area at the bottom coal seam to the adjacent goaf area; when the width exceeds 20 m, the water cannot enter the adjacent goaf area through the bottom coal pillar. On the basis of CFD simulation study on seepage properties of coal/rock pillars between goafs, this paper conducts calculations for all the goafs in the 4-2 coal-panel block of Wanli No. 1 Mine and reveals the seepage path and seepage law in the underground reservoir of this mine.

Impacts of coal-fired power plants for energy generation on environment and future implications of energy policy for Turkey.

Turkish government aimed to increase the installed capacities of coal-fired power plants (CFPPs) according to several policies and strategic plans published in recent years. Energy production from CFPPs and subsidizing the coal sector were selected for reducing the import dependency as a cheaper option. CFPPs with gaseous emissions as well as fly ash and fine dust, along with ash storage, coal storage, and coal mining operations and water use for cooling of the plants, affect the environmental quality. Hence, the health of inhabitants of the environment is affected. CFPPs to be built, according to strategic plans, will emit a significant amount of greenhouse gases (GHGs) and would severely undermine the targets for a 1.5 ℃ or 2 ℃ warmer world. Subsidies to the coal sector, along with exemptions from environmental regulations, combined with slower growth of energy production from renewable energy sources (RES), may lead to a path dependence on coal, while the rest of the world increases their energy production from RES. This study demonstrates the concrete examples of pollution caused by CFPPs in Turkey, along with health effects with the addition of policy context toward utilization of CFPPs, to point out the risks these plants constitute both for the environment and economy. Increasing the share of RES in the energy mixture is particularly important for Turkey due to being in a geographical region that is highly vulnerable to climate change effects. This study also briefly discusses how the increase of RES and de-carbonization in Turkey could be conducted in the short- and long-term, upon the literature provided.

Improved thin-film-composite forward-osmosis membrane for coal mine water purification

During the emergency rescue, such as coal mining disasters, potable water was the primary factor to ensure the safety of people trapped underground, and it was easy to be obtained by the filtration of coal mine water. As a membrane separation technology, forward osmosis (FO) membranes were expected to be used in the emergency filtration of coal mine water with higher contents of SO42− and F−. In this paper, a thin film composite (TFC) FO membrane was prepared by phase conversion and interfacial bonding methods, and the influence of compound modification by TiO2, polyvinyl alcohol (PVA) and polydopamine (PDA) on the morphology and permeability of the TFC FO membrane was studied. The results show that the large size TiO2 (50 nm) was only physically deposited on the polysulfone (PSF) membrane, and PVA increased the binding strength of the PDA membrane to the polyamide (PA) membrane. As a result, 2 wt% TiO2 and 2 wt% PVA and PDA co-doping led to a low water contact angle of 27° and a high FO water flux performance of 12.9 LM−2H−1 using a 2 M NaCl draw solution. Furthermore, the composite membrane showed better hydrophilicity, and the rejection of SO42− and F− were 92.1% and 89.3%, respectively, indicating that TiO2 improved the internal channels of the TFC FO membrane and PVA and PDA increased the hydrophilicity of the PA layer. Therefore, the novel TFC FO membrane exhibited good rejection and reproducibility, and this study demonstrated that TFC FO membrane was a good candidate for the emergency filtration of coal mine water.

Evaluating water-yield property of karst aquifer based on the AHP and CV

In order to ensure the safety of mine production, it is of great practical significance to make a reasonable evaluation of the water-yield property (WYP) of a karst aquifer. In this paper, we selected fault-lines distribution, fault-scale index, aquifer thickness, water pressure, consumption of rinsing liquid, and hydraulic conductivity as the evaluation indexes to analyze the WYP of a karst aquifer. Meanwhile, the analytic hierarchy process (AHP) is used to calculate the subjective weight of indexes, and the coefficient of variation (CV) is used to calculate the objective weight of indexes. Combined with GIS, a multi-factor composite superposition is carried out to evaluate the WYP of a karst aquifer. The reliability of the research results is verified by the specific yield. Besides, for improving the reliability of evaluation results, the chemical composition of karst water was discussed. The results show that the selection of indexes is reasonable and the AHP–CV method is effective to evaluate the WYP of a karst aquifer. Therefore, on the premise of reasonable index selection, the evaluation models of AHP and CV can be used to evaluate the WYP of a karst aquifer and provide reference for coal mine water control measures.

Intelligent prediction of coal mine water inrush based on optimized SAPSO-ELM model under the influence of multiple factors

Mine water inrush is affected by many factors such as geological structure and fracture zone. However, there may be overlap among these factors, leading to uncertainty, fuzzy similarity and nonlinear relationship among most of them. Therefore, the traditional mathematical model is not ideal to predict water inrush. This paper proposes an intelligent model for predicting water inrush from coal floor based on simulated annealing particle swarm optimization-extreme learning machine (SAPSO-ELM). Based on 144 groups of learning data and 36 groups of predictive validation data, the proposed model extracted common factors from 14 geological factors that might be related to water inrush in a mining area, so as to reduce information interaction among discriminant indexes. In this paper, simulated annealing particle swarm optimization (SAPSO) is innovatively used to optimize the model parameters and compared with other intelligent models (SVM, BPNN, PSO-ELM and ELM) for the learning prediction of the same data. The results show that the common factors extracted from the original variables contain most of the comprehensive information and can reduce information redundancy. Compared with traditional intelligent models (SVM, BPNN, PSO-ELM and ELM), the proposed model improves the computational efficiency of convergence, and the prediction accuracy is higher. It is proved that SAPSO-ELM intelligent algorithm is indeed scientific and has broad application prospect in result prediction induced by complex multi-factors.

A real-time monitoring temperature-dependent risk index for predicting mine water inrush from collapse columns through a coupled thermal–hydraulic-mechanical model

Advance forecast of water inrush can help ensure operational safety in underground engineering. In this study, a coupled thermal–hydraulic-mechanical (THM) model is developed to simulate the process of water inrush from collapse columns in coal mines with complex geological environments. Specifically, nonlinear fluid flow and heat transfer in porous media associated with the erosion and damage of collapse columns are considered. This numerical model is validated against water-inrush field data from two coal mines with regard to flow rate. Fluid pressure and temperature profiles over time are also investigated. There is a water pressure accumulation phenomenon in hidden collapse columns. Temperature is found to change more significantly than velocity in the early stages of water inrush. In addition, the spatial variation of temperature can be divided into three zones during the process of water inrush. According to the rules governing the spatio-temporal variation of temperature, a novel method utilizing a real-time monitoring temperature-dependent risk index (TRI) and a water inrush induced increasing temperature zone (WIT) is proposed to determine whether and where water inrushes will occur. This study demonstrates how this novel method can predict water inrush and overcome the main limitations in previous studies where temperature was used as a predictor. This method has the potential to be applied in practice to better understand the risks related to coal mine management and water inrush and thus improves mine safety.

Prediction of water source and water volume of underground reservoir in coal mine under multiple aquifers

Abstract The role of coal mine underground reservoirs (CMUR) in ‘guide storage and use’ greatly solves the problem of mine water waste. Replenishment and prediction of reservoir water sources provide an important support for the successful development of key technologies concerning CMUR. To study water replenishment for CMUR, the hydrogeological conditions of the Shendong mining area were investigated as an example. Based on the relationship between the development height of the ‘two belts’ of shallow coal seams and the relative occurrence of location of aquifers, the aquifers are generalized and classified according to occurrences location. Taking Bulianta coal mine as the research background, a discrete element fluid–solid coupling numerical simulation model is constructed to analyze the development characteristics of mining-induced fractures after coal seam mining, and the water replenishment channel of the CMUR is determined. On this basis, analysis is made on the change law of water pressure in the aquifer, aquifuge and coal seam roof under mining action. Taking hydraulic head pressure and water velocity as the judgment basis, prediction and evaluation are made on the water replenishment capacity of CMUR. The research results can provide references for coal mine safety production and mine water protection and utilization.

Risk assessment of coal mine water inrush based on PCA-DBN

To provide an effective risk assessment of water inrush for coal mine safety production, a BP neural network prediction method for water inrush based on principal component analysis and deep confidence network optimization was proposed. Because deep belief network (DBN) is disadvantaged by a long training time when establishing a high-dimensional data classification model, the principal component analysis (PCA) method is used to reduce the dimensionality of many factors affecting the water inrush of the coal seam floor, thus reducing the number of variables of the research object, redundancy and the difficulty of feature extraction and shortening the training time of the model. Then, a DBN network was used to extract secondary features from the processed nonlinear data, and a more abstract high-level representation was formed by combining low-level features to find the expression of the nonlinear relationship between the characteristics of water in bursts. Finally, a prediction model was established to predict the water inrush in coal mines. The superiority of this method was verified by comparing the prediction of the actual working face with the actual situation in typical mining areas of North China. The prediction accuracy of coal mine water inrush obtained by this algorithm is 94%, while the prediction accuracy of traditional BP algorithm is 70%, and the prediction accuracy of SVM algorithm is 88%.

Effect of Cone-Plate Clarifier Structure Parameters on Flocculation Efficiency

In this study, a coal mine water flocculation system was established. A series of flocculation tests were carried out at different structural parameters (cylinder height, cone-plate insertion depth and cone-plate spacing) to better investigate the effect of the cone-plate clarifier on coal mine water treatment performance. Sixteen sampling points were set up in the system for data monitoring to generate the required data. The cone-plate clarifier was divided into five zones for flocculation analysis. The increased cylinder height facilitated the flocculation of particles in the micro flocculation zone and the settling of particles in the settlement zone. The chemicals used are polyaluminum chloride (PACl), Fe3O4 and polyacrylamide (PAM), corresponding to doses of 60 mg/L, 40 mg/L and 6 mg/L, respectively. Insufficient insertion depth of the cone-plate will cause the small flocs that have not been fully flocculated to enter the exit pipe zone directly through the cone-plate, while too much insertion depth will cause the large floc in the settlement zone to re-enter the exit pipe zone. The flocculation effect of small flocs increased as the cone-plate spacing decreased, which is consistent with the shallow pool theory. When the cone plate spacing was too narrow, the amount of fluid was reduced and the increase in fluid velocity reduced the flocculation effect. Curve fitting was conducted for Suspended solids(SS) and turbidity removal efficiency under each structural parameter to derive the variation of SS and turbidity removal efficiency under different structural parameters. The regression models of SS and turbidity removal efficiency on the cylinder height, cone-plate insertion depth and cone-plate spacing were established based on the curve fitting results, and the regression models were verified to be well fitted based on the comparison of experimental results. Finally, the optimal values of SS and turbidity removal efficiency were found based on the regression model. The flow rate of the cone-plate clarifier is 0.6 m3/h. The SS removal efficiency reached 96.82% when the cylinder height was 708 mm, the cone-plate insertion depth was 367 mm and the cone-plate spacing was 26 mm. The turbidity removal efficiency reached 86.75% when the cylinder height was 709 mm, the cone-plate insertion depth was 369 mm and the cone-plate spacing was 26 mm.