Clarifying the correlations between hydraulic indicators evaluating the hydraulic performance of free water surface constructed wetlands.

Previous studies have shown a strong linear correlation between the common hydraulic indicators of free water surface constructed wetlands (FWS CWs), which results in the waste of computing resources and confusion in evaluating the hydraulic performance of FWS CWs. There is an urgent need to define a relatively independent and authoritative hydraulic indicator. In this study, based on three years' data, the correlations among five representative hydraulic indicators, that is, short-circuit index (φ10), Morrill dispersion index (MDI), effective volume ratio (e), moment index (MI), and hydraulic efficiency (λe), were analyzed by combining a variety of methods. The results of the correlation analysis and principal component analysis clearly showed the positive correlations among φ10, e, MI, and λe (p < 0.01), and the strong negative correlations between MDI and the remaining four indexes, which were further confirmed by redundancy analysis (RDA). Most importantly, the significant correlations between MI vs e and φ10 vs e were proved through rigorous mathematical reasoning for the first time. Besides, the results of RDA indicated that the studied design parameters, namely, water depth, hydraulic loading rate, plant spacing, aspect ratio, layout of inlet and outlet, and plant species, could generally explain the variation in hydraulic indicators. The layout of inlet and outlet displayed positive effects on hydraulic performance, and the water depth exhibited negative effects. Combining the clarity of physical meaning, convenience of calculation, and universality of reflecting both hydraulic and treatment performances, e was recommended as the most authoritative hydraulic indicator to evaluate hydraulic performance. The clustering results based on e were highly consistent with those based on the comprehensive principal component score. Wetlands with a combination of lower water depth and better layout of inlet and outlet usually have better hydraulic performance. This study successfully revealed the significant correlations among hydraulic indicators and their sources, and recommended a unique hydraulic indicator to authoritatively evaluate the hydraulic performance of FWS CWs.

Storages and leaching losses of soil water dissolved CO2 and N2O on typical land use hillslopes in southeastern hilly area of China.

The dynamics of soil water dissolved CO2 and N2O are important in determining the fates of soil CO2 and N2O. However, related mechanisms and processes have been rarely revealed. In this study, storages and leaching losses of soil water dissolved CO2 and N2O were investigated on the tea garden (TG) and bamboo forest (BF) hillslopes. Soil water storage and leaching flux were simulated by the HYDRUS-3D model and the soil water dissolved CO2 and N2O concentrations were acquired by field monitoring. Results showed that the storages of soil water dissolved CO2 and N2O ranged from 1.30 to 14.86 kg C ha-1 and 0.24 to 388.99 g N ha-1 on the TG hillslope, respectively, while they ranged from 0.49 to 52.29 kg C ha-1 and 0.50 to 14.22 g N ha-1 on the BF hillslope, respectively. The annual leaching loss of soil water dissolved CO2 and N2O were 26.17 kg C ha-1 and 29.46 g N ha-1, respectively, on the TG hillslope, while they were 49.51 kg C ha-1 and 4.35 g N ha-1 on the BF hillslope, respectively. The dissolved CO2 leaching loss mainly occurred in summer, especially in July on both hillslopes. Peaks of dissolved N2O leaching loss on the TG hillslope were observed after the application of basal fertilizer, accompanying with precipitation events. Instead, peaks of dissolved N2O leaching loss on the BF hillslope were observed in summer. The main influencing factors of dissolved CO2 and N2O storages were temperature, precipitation, and fertilization, with total effects generally >0.30. However, that of the dissolved CO2 and N2O leaching losses was the precipitation, with total effects >0.57. Dissolved CO2/N2O concentration was more important than soil water storage in determining the dissolved CO2/N2O storage, while the leaching flow rate was more crucial than dissolved CO2/N2O concentration in determining the dissolved CO2/N2O leaching loss. These findings expanded our knowledge of sources and sinks of greenhouse gases on the terrestrial ecosystem.

Quantitative prediction of the hydraulic performance of free water surface constructed wetlands by integrating numerical simulation and machine learning.

Quantitative prediction of the design parameter-influenced hydraulic performance is significant for optimizing free water surface constructed wetlands (FWS CWs) to reduce point and non-point source pollution and improve land utilization. However, owing to limitations of the test conditions and data scale, a quantitative prediction model of the hydraulic performance under multiple design parameters has not yet been established. In this study, we integrated field test data, mechanism model, statistical regression, and machine learning (ML) to construct such quantitative prediction models. A FWS CW numerical model was established by integrating 13 groups of trace data from field tests. Subsequently, training, test and extension datasets comprising 125 (5^3), 25 (L25(56)) and 16 (L16(44)) data points, respectively, were generated via numerical simulation of multi-level value combination of three quantitative design parameters, namely, water depth, hydraulic loading rate (HLR), and aspect ratio. The short circuit index (φ10), Morrill dispersion index (MDI), hydraulic efficiency (λ) and moment index (MI) were used as representative hydraulic performance indicators. Training set with large samples were analyzed to determine the variation rules of different hydraulic indicators. Based on the control variable method, φ10, λ, and MI grew exponentially with increasing aspect ratio whereas MDI showed a decreasing trend; with increasing water depth, φ10, λ, and MI showed polynomial decreases whereas MDI increased; with increasing HLR, φ10, λ, and MI slowly increased linearly whereas MDI showed the opposite trend. Finally, we constructed models based on multivariate nonlinear regression (MNLR) and ML (random forest (RF), multilayer perceptron (MLP), and support vector regression. The coefficients of determination (R2) of the MNLR and ML models fitting the training and test sets were all greater than 0.9; however, the generalization abilities of different models in the extension set were different. The most robust MLP, MNLR without interaction term, and RF models were recommended as the preferred models to hydraulic performance prediction. The extreme importance of aspect ratio in hydraulic performance was revealed. Thus, gaps in the current understanding of multivariate quantitative prediction of the hydraulic performance of FWS CWs are addressed while providing an avenue for researching FWS CWs in different regions according to local conditions.

Machine learning exhibited excellent advantages in the performance simulation and prediction of free water surface constructed wetlands.

Optimizing the design and operation parameters of free water surface constructed wetlands (FWS CWs) in runoff regulation and wastewater treatment is necessary to improve the comprehensive performance. In this study, nine machine learning (ML) algorithms were successfully developed to optimize the parameter combinations for FWS CWs. The scale effect of surface area on wetland performance was determined based on consistently smaller predictions (-6.2% to -28.9%) of the nine well-established ML algorithms. The models most suitable for FWS CW performance simulation and prediction were random forest and extra trees algorithms because of their high R2 values (0.818 in both) with the training set and low mean absolute relative errors (4.7% and 3.8%, respectively) with the test set. Results from feature analysis of the six tree-based algorithms emphasized the importance of water depth and layout of inlet and outlet, and revealed the negligible effect of the aspect ratio. Feature importance and partial dependence analysis enhanced the interpretability of the tree-based algorithms. The proposed ML algorithms enabled the implementation of an extended scenario at a low cost in real time. Therefore, ML algorithms are suitable for expressing the complex and uncertain effects of the design and operation parameters on the performance of FWS CWs. Acquiring datasets consisting of more extensive, uniform, and unbiased parameter combinations is crucial for developing more robust and practical ML algorithms for the optimal design of FWS CWs.

Utilizing artificial neural network to simulate and predict the hydraulic performance of free water surface constructed wetlands.

Optimizing the hydraulic performance of free water surface constructed wetlands (FWS CWs) is of great economic and ecological value. However, there is a complex nonlinear relationship between the hydraulic performance and design parameters of FWS CWs. In this study, an artificial neural network (ANN) was applied to simulate and predict the hydraulic performance corresponding to different combinations of design parameters, and orthogonal design L9 (34) was used to determine the optimal combination of the important hyperparameters of the ANN. Based on the convenient scenario prediction ability of ANN, sensitivity analysis of different design parameters was carried out by the control variate method and full factor experiment. The results showed that the combination of 3 hidden layers, 15 neural nodes in each hidden layer, 0.001 learning rate, and 8 batch sizes was optimal for the established ANN model, achieving a coefficient of determination of 0.828 in the validation set and a satisfactory prediction effect in the test set. The narrow feature distribution interval in the training set restricted the generalization ability of the ANN model to some extent. Of the four continuous design parameters, the water depth and aspect ratio had an important influence on the effective volume ratio. The layout of inlet and outlet was the most influential design parameter, as confirmed by the full factor experiment of five factors and four levels. The established ANN allowed real-time implementation in an extended scenario at a low cost. This study suggests that the ANN can simultaneously project complex and uncertain effects of several design parameters on wetland performance. In future research, acquiring further comprehensive, impartial, and unbiased experimental datasets is necessary to establish a more robust and generalizing ANN model that can guide the optimal design of FWS CWs.

Improved solute transport and pollutant degradation model of free water surface constructed wetlands considering significant linear correlation between model parameters.

To unify the structures of solute transport and pollutant degradation models and evaluate the wetland performance conveniently, a pollutant degradation model combining first-order kinetics with the hybrid solute transport model (plug flow with dispersion + continuous stirred-tank reactor, PFD + CSTR) was developed. Orthogonal tests revealed significant correlation between the model parameters, and the original models were optimized via linear substitution of parameters. The improved PFD + CSTR solute transport model exhibited a satisfactory fit with the original model, and the average relative errors of the determination coefficient (R2) and correlation coefficient were <5%. The multiple linear regressions between the hydraulic indicators and model parameters were reconstructed and exhibited consistent structures between different stages. The degradation constant kaTN between the original and improved models exhibited high consistency (R2 = 0.982). Conclusively, the improved models exhibited good consistency with the original models and allowed rapid and accurate performance evaluation.

Response of solute transport model parameters to the combination of multiple design parameters and their quantitative expression with hydraulic indicators of FWS-constructed wetlands.

Solute transport models and hydraulic indicators are commonly used to assess the flow pattern of free water surface-constructed wetlands (FWS CWs). However, the relationship between solute transport models and hydraulic performance remains poorly understood. The hybrid model comprised of plug flow with dispersion and continuous stirred tank reactors (PFD + CSTRs) was applied in this study. The variation rules of model parameters, namely the flow ratio of the mixed zone f, volume ratio of the mixed zone z, dispersion number D, and number of mixed tanks N, were obtained by fitting of the normalized tracer data of orthogonal tests. The coefficients of determination (R2) exceeded 0.7 and the correlation coefficient (r) surpassed 0.8. The results demonstrated satisfactory hydraulic performance and purification effect, with high hydraulic and water quality indicators. Water depth was the principal design parameter negatively affecting f and z, whereas the layout of in- and outlet positively influenced D and N. The R2 of the model parameters f, z, and D on most hydraulic indicators were above 0.5. Significantly positive correlations existed between the model parameters f, z, and D and the hydraulic indicators including the short-circuit index φ10, effective volume ratio e, and moment index MI. The quantitative links between model parameters and hydraulic indicators were established. Based on the significant correlations between design parameters, hydraulic indicators, and model parameters, it would be more convenient to evaluate the hydraulic performance of FWS CWs corresponding to specific design parameters. Graphical abstract.

Correction to: Response of solute transport model parameters to the combination of multiple design parameters and their quantitative expression with hydraulic indicators of FWS-constructed wetlands.

The correct Fig. 6 is presented in this paper.

Improved test to determine design parameters for optimization of free surface flow constructed wetlands.

Orthogonal tests were performed to assess the effect of design parameters on hydraulic and treatment performances of constructed wetlands. The results showed that water depth, layout of in- and outlet, flow rate, and aspect ratio mainly affected hydraulic performance, and water depth, plant spacing, and layout of in- and outlet mainly affected treatment performance. Optimal integrated performance was achieved with combination of 20-30 cm water depth, five evenly distributed inlets and one middle outlet, a flow rate of 0.4-0.55 m3/h, 20-cm plant spacing, a 1.125:1 aspect ratio, and planted with Scripus tabernaemontani. The average treatment performances of 27.2%, 16.3%, and 30.7% removal rates were received for total nitrogen, total phosphorus, and total suspended solid, respectively. The design parameters that significantly influenced hydraulic performance did not significantly influence treatment performance. Various hydraulic and purification indicators displayed extremely significant correlations. There was a significant correlation between hydraulic performance and mass removal capacity.

Test study of the optimal design for hydraulic performance and treatment performance of free water surface flow constructed wetland.

Orthogonal tests with mixed levels of design parameters of a free water surface flow constructed wetland were performed to assess their effect on hydraulic and treatment performance, and discover the relationship between the design parameters and the two performances. The results showed that water depth, plant spacing, and layout of in- and outlet mainly affected the two performances. Under 40cm depth, central pass of in- and outlet, 1.8m3/h flow rate, 20cm plant spacing, 2:1 aspect ratio, and Scripus tabernaemontani as the plant species, treatment performance of 5.3% TN, 6.1% TP and 15.6% TSS removal efficiencies and a high hydraulic performance of 0.854e, 0.602MI were achieved. There was no significant correlation between the design parameters and the two performances. The relationship among various hydraulic indicators and that among the purification indicators displayed extremely significant correlation. However, there was no significant correlation between hydraulic and treatment performance.

[Effect of water depths on hydraulic performance of pond wetlands].

Pond wetlands have been widely used in the treatment of drainage water from paddy fields. However, wetland hydraulic performance and purification effects are affected by many factors, such as water depth, flow rate, aspect ratio and vegetation distribution, and the better understanding of these factors would be helpful to improve the quality of wetland design, operation and management. This paper analyzed the effect of three different water depths (20, 40 and 60 cm) on the hydraulic performance of pond wetland through the dye tracer experiments with Rhodamine WT. The hydraulic indices, i. e., effective volume ratio, nominal serial complete mixing tanks (N), hydraulic efficiency (λ), were selected for analysis through the hydraulic residence time distribution (RTD) curve. The results showed that the effective volume rate rose from 0.421 to 0.844 and the hydraulic efficiency from 0.281 to 0.604 when the water depth declined from 60 cm to 20 cm. This indicated that the wetland hydraulic performance improved as the water depth decreased. In addition, the hydraulic performance of the first half of the wetland was significantly better than that of the second half. The flow regime of the first half approached complete mixing because of the mixing index (N) approaching 1 and its effective volume rate was above 0.9 when the water depth was relatively low (20 and 40 cm). The normalized RTD curves demonstrated a good agreement between moment analysis parameters and hydraulic parameters, and a great consistency between the hydraulic parameters and moment index which was not affected by tail truncation error. The experimental study concluded that a lower water depth was favorable to improve the hydraulic performance of pond wetlands.