Oxygen Gradients and Structure of the Ciliate Assemblages in Floodplain Lake

This paper presents the results of studies on the structure of the ciliate population in a freshwater lake. The classification of the ciliated communities based on the analysis of the distribution of ciliate population density in the lake along the oxygen gradients, taking into account their oxygen preferences, was proposed. It was shown that the distribution of ciliated protozoa in the space of a reservoir is determined not by such spatial units as the water column, bottom, and periphytal, but by the oxygen gradients. Four types of habitats with different oxygen regimes were distinguished: With stably high oxygen concentration, stably low oxygen concentration, stably oxygen-free conditions, and conditions with a high amplitude of diurnal oxygen variations. The location of these habitats in the space of the lake and their seasonal changes were determined. On the basis of the quantitative development of ciliate populations, zones of optima and tolerance ranges of some ciliate species in the oxygen gradient were established. The oxygen preferences were established for the species from four distinguished assemblages: Microoxyphilic, oxyphilic, euryoxyphilic, and anoxyphilic (anaerobic). The presence or the absence of a certain type of assemblage in the reservoirs depends solely on the parameters of the oxygen gradients. The diversity of the ciliated protozoa in water bodies also depends on the stability and diversity of the oxygen gradients

Assessment of wastewater treatment plant effluent impact on the ecosystem of the river on the basis of the quantitative development of ciliated protozoa characteristic of the aeration tank

The work is devoted to the task of simplifying the assessment of the effect of effluents from treatment facilities on the river hydrobiocenosis. The studies were carried out on the mountain river Uzh (Uzhgorod, Ukraine). Our approach to assessing the impact of waste treatment facilities on the river receiver is based on the estimate of the similarity of species composition and quantitative characteristics of populations of organisms from the aerotank and from the river. It is shown that the quantitative development of populations of species of ciliates from the aeration tank is a good indicator for assessing the degradation of organic matter coming with wastewater. The use of qualitative and quantitative characteristics of the protozoa from the wastewater treatment plant as a criterion for assessing the quality of the environment in the area of wastewater discharge showed their representativeness and effectiveness. The use of a limited number of species makes it possible to conduct an express assessment of the effect of effluents on receiving reservoirs for specialists working with activated sludge in the laboratories of treatment facilities

Contribution of prokaryotes and eukaryotes to CO2 emissions in the wastewater treatment process

Reduction of the greenhouse effect is primarily associated with the reduction of greenhouse gas (GHG) emissions. Carbon dioxide (CO2) is one of the gases that increases the greenhouse effect - it is responsible for about half of the greenhouse effect. Significant sources of CO2 are wastewater treatment plants (WWTPs) and waste management, with about 3% contribution to global emissions. CO2 is produced mainly in the aerobic stage of wastewater purification and is a consequence of activated sludge activity. Although the roles of activated sludge components in the purification process have been studied quite well, their quantitative contribution to CO2 emissions is still unknown. The emission of CO2 caused by prokaryotes and eukaryotes over the course of a year (taking into account subsequent seasons) in model sequencing batch reactors (SBR) is presented in this study. In this work, for the first time, we aimed to quantify this contribution of eukaryotic organisms to total CO2 emissions during the WWTP process. It is of the order of several or more ppm. The contribution of CO2 produced by different components of activated sludge in WWTPs can improve estimation of the emissions of GHGs in this area of human activity

Analysis of Sewer Network Performance in the Context of Modernization: Modeling, Sensitivity, and Uncertainty Analysis

Specific flood volume and degree of flooding are important parameters for evaluating the performance of stormwater networks. Hydrodynamic models are usually used to calculate these important measures, but this task requires the collection of detailed data on land use, the sewer network, rainfall, and flows, which are not always possible to obtain. The present research consists in the development of a methodology, using the USEPA Stormwater Management Model (SWMM), for simulating the performance of a stormwater network to determine whether it is in need of modernization. This determination is based on independent variables including rainfall data, catchment retention, and channel capacity. A logistic regression was developed to assess the sewer network performance based on simulation of specific flood volume and degree of flooding in the context of modernization. An extended sensitivity analysis was also used to assess the influence of rainfall intensity on the results of sensitivity coefficient calculations for the calibrated SWMM parameters. Using the extreme gradient boosting method, a tool has been developed to optimize the combination of SWMM parameters, reducing the uncertainty of simulation results, which can be used in the selection of their measurement methods prior to model development. It has been shown that, using the logistic regression model, it is possible to rapidly simulate the operation of a stormwater system to assess its need for modernization. It was confirmed that an increase in rainfall intensity leads to a significant decrease in the values of the calculated sensitivity coefficients associated with the SWMM parameters. The highest sensitivity coefficient was shown for a correction coefficient for percentage of impervious areas; for rainfall intensity 33-133 L.(s.ha)(-1) varied from 1.45 to 12.38. This result leads to a method for selecting specific rainfall events for calibration of the model, thereby improving the ability to assess the performance of the stormwater system. Interestingly, however, for the exemplary catchment in Kielce, Poland, the generalized likelihood uncertainty estimation (GLUE) method was used, combined with the XGboost machine learning technique, to determine that the reliability of the SWMM parameters has a negligible impact on the probability of a stormwater network failure. (C) 2022 American Society of Civil Engineers

Influence of urban catchment characteristics and rainfall origins on the phenomenon of stormwater flooding: Case study

This work presents a methodology for analyzing the influence of urbanization in a long-term approach on the number of floods in an urban catchment. The mathematical model presented for predicting the multiannual number of stormwater floods accounts for dynamic changes in the urban catchment in the subsequent years covered by the simulations. Logistic regression was applied to predict flooding occurring during rainfall events. The model may be applied to catchments with different characteristics. The assumed solution allows the development of early warning systems by modeling the occurrence of stormwater flooding in a studied catchment area based on the identification of the rainfall origin. To verify the simulations with a mathematical model, an innovative concept based on a hydrodynamic model is used; this concept includes the changes in the impervious area that occur during the simulation period

Advanced sensitivity analysis of the impact of the temporal distribution and intensity of rainfall on hydrograph parameters in urban catchments

Knowledge of the variability of the hydrograph of outflow from urban catchments is highly important for measurements and evaluation of the operation of sewer networks. Currently, hydrodynamic models are most frequently used for hydrograph modeling. Since a large number of their parameters have to be identified, there may be problems at the calibration stage. Hence, sensitivity analysis is used to limit the number of parameters. However, the current sensitivity analytical methods ignore the effect of the temporal distribution and intensity of precipitation in a rainfall event on the catchment outflow hydrograph. This article presents a methodology of constructing a simulator of catchment outflow hydrograph parameters (volume and maximum flow). For this purpose, uncertainty analytical results obtained with the use of the GLUE (generalized likelihood uncertainty estimation) method were used. A novel analysis of the sensitivity of the hydrodynamic catchment models was also developed, which can be used in the analysis of the operation of stormwater networks and underground infrastructure facilities. Using the logistic regression method, an innovative sensitivity coefficient was proposed to study the impact of the variability of the parameters of the hydrodynamic model depending on the distribution of rainfall, the origin of rainfall (on the Chomicz scale), and the uncertainty of the estimated simulator coefficients on the parameters of the outflow hydrograph. The developed model enables the analysis of the impact of the identified SWMM (Storm Water Management Model) parameters on the runoff hydrograph, taking into account local rainfall conditions, which have not been analyzed thus far. Compared with the currently developed methods, the analyses included the impact of the uncertainty of the identified coefficients in the logistic regression model on the results of the sensitivity coefficient calculation. This aspect has not been taken into account in the sensitivity analytical methods thus far, although this approach evaluates the reliability of the simulation results. The results indicated a considerable influence of rainfall distribution and intensity on the sensitivity factors. The greater the intensity and rainfall were, the lower the impact of the identified hydrodynamic model parameters on the hydrograph parameters. Additionally, the calculations confirmed the significant impact of the uncertainty of the estimated coefficient in the simulator on the sensitivity coefficients. In the context of the sensitivity analysis, the obtained results have a significant effect on the interpretation of the relationships obtained. The approach presented in this study can be widely applied at the model calibration stage and for appropriate selection of hydrographs for identification and validation of model parameters. The results of the calculations obtained in this study indicate the suitability of including the origin of rainfall in the sensitivity analysis and calibration of hydrodynamic models, which results from the different sensitivities of models for normal, heavy, and torrential rain types. In this context, it is necessary to first divide the rainfall data by origin, for which analyses will be performed, including sensitivity analysis and calibration.Considering the obtained results of the calculations, at the stage of identifying the parameters of hydrodynamic models and their validation, precipitation conditions should be included because, for the precipitation caused by heavy rainfall, the values of the sensitivity coefficients were much lower than for torrential ones. Taking into account the values of the sensitivity coefficients obtained, the calibration of the models should not only cover episodes with high rainfall intensity, since this may lead to calculation errors at the stage of applying the model in practice (assessment of the stormwater system operating conditions, design of reservoirs and flow control devices, green infrastructure, etc.)