Model-based knowledge acquisition in environmental decision support system for wastewater integrated management

Intelligent Tools to Monitor, Control and Predict Wastewater Reclamation and Reuse

Contemporary wastewater reclamation units entail several diverse treatment and extraction processes, with a multitude of monitored quality characteristics, controlled by a variety of key operational parameters directly affecting the efficiency of treatment. The conventional optimization of this highly complex system is time- and energy- consuming, frequently relying on intuitive decision making by operators, and does not predict or forecast efficiency changes and system maintenance. In this paper, we introduce intelligent solutions to enhance the operational control of the unit with minimal human intervention and to develop an AI-powered DSS that is installed atop the sensors of a water treatment module. The DSS uses an expert model, both to assess the quality of water and to offer suggestions based on current values and future trends. More specifically, the quality of the produced water was successfully visualized, assessed and rated, based on a set of input operational variables (pH, TOC for this case), while future values of monitored sensors were forecasted. Additionally, monitoring services of the DSS were able to identify unexpected events and to generate alerts in the case of observed violation of operational limits, as well as to implement changes (automatic responses) to operational parameters so as to reestablish normal operating conditions and to avoid such events in the future. Up to now, the DSS suggestion and forecasting services have proven to be adequately accurate. Though data are still being collected from early adopters, the solution is expected to provide a complete water treatment solution that can be adopted by a vast range of parties.

Decision Support Concept to Selection of Wastewater Treatment Plant Location—the Case Study of Town of Kutina, Croatia

In environmental projects, decision-making can be a complex and challenging task due to the in-built existence of compromises between environmental, socio-political, and economic factors. This paper explores a systematic approach to developing a decision support concept that includes the analysis of wastewater treatment problems, knowledge acquisition, and the identification and evaluation of criteria that bring forth an optimal solution to the location selection of wastewater treatment plants (WWTPs). The objective of this research is to develop a decision support concept (DSC) to aid in the planning phases of complex engineering projects, such as the construction of WWTP. The development of the concept starts with an assessment of the issue and an identification of relevant stakeholders accepting their different views and attitudes in an attempt to resolve this issue. The DSC was tested on a real case project—WWTP location selection within the town of Kutina, Croatia. Results indicate that it is possible to develop such a concept based on multicriteria methods on which decision-makers can rely.

Operator decision support system for integrated wastewater management including wastewater treatment plants and receiving water bodies

An operator decision support system (ODSS) is proposed to support operators of wastewater treatment plants (WWTPs) in making appropriate decisions. This system accounts for water quality (WQ) variations in WWTP influent and effluent and in the receiving water body (RWB). The proposed system is comprised of two diagnosis modules, three prediction modules, and a scenario-based supporting module (SSM). In the diagnosis modules, the WQs of the influent and effluent WWTP and of the RWB are assessed via multivariate analysis. Three prediction modules based on the k-nearest neighbors (k-NN) method, activated sludge model no. 2d (ASM2d) model, and QUAL2E model are used to forecast WQs for 3 days in advance. To compare various operating alternatives, SSM is applied to test various predetermined operating conditions in terms of overall oxygen transfer coefficient (Kla), waste sludge flow rate (Qw), return sludge flow rate (Qr), and internal recycle flow rate (Qir). In the case of unacceptable total phosphorus (TP), SSM provides appropriate information for the chemical treatment. The constructed ODSS was tested using data collected from Geumho River, which was the RWB, and S WWTP in Daegu City, South Korea. The results demonstrate the capability of the proposed ODSS to provide WWTP operators with more objective qualitative and quantitative assessments of WWTP and RWB WQs. Moreover, the current study shows that ODSS, using data collected from the study area, can be used to identify operational alternatives through SSM at an integrated urban wastewater management level.

Ecosystem-based management of a Mediterranean urban wastewater system: a sensitivity analysis of the operational degrees of freedom

Urban wastewater systems discharge organic matter, nutrients and other pollutants (including toxic substances) to receiving waters, even after removing more than 90% of incoming pollutants from human activities. Understanding their interactions with the receiving water bodies is essential for the implementation of ecosystem-based management strategies. Using mathematical modeling and sensitivity analysis we quantified how 19 operational variables of an urban wastewater system affect river water quality. The mathematical model of the Congost system (in the Besòs catchment, Spain) characterizes the dynamic interactions between sewers, storage tanks, wastewater treatment plants and the river. The sensitivity analysis shows that the use of storage tanks for peak shaving and the use of a connection between two neighboring wastewater treatment plants are the most important factors influencing river water quality. We study how the sensitivity of the water quality variables towards changes in the operational variables varies along the river due to discharge locations and river self-purification processes. We demonstrate how to use the approach to identify interactions and how to discard non-influential operational variables.

Field validation of a new low-cost method for determining occurrence and duration of combined sewer overflows

Combined sewer overflow (CSO) events produced in combined sewer systems (CSS) during wet weather conditions are a threat for the receiving water bodies. The large number of CSO structures normally present in a CSS makes that the monitoring of the complete CSO network in a simultaneous way would drastically increase the investment costs. In this paper, a new methodology is presented aiming to characterize the occurrence and duration of CSO events by means of low-cost temperature sensors. Hence, a large number of CSO structures can be simultaneously monitored and the system can be characterized as a whole. The method assumes temperature differences between the overflowing mix of wastewater and stormwater and the sewer gas phase, so the temperature shift produced during a rainfall episode is related to a CSO event occurrence. The method has been tested and validated in La Garriga CSS (Spain) where the temperature at 13 CSO weirs was monitored for a period of 1 year (57 rainfall episodes). For the whole set of CSO events, occurrence and duration were successfully determined in 80% of cases. Advantages, limitations and potential applications of the method are discussed at the end of the paper.

Applying global sensitivity analysis to the modelling of flow and water quality in sewers

While several approaches for global sensitivity analysis (GSA) have been proposed in literature, only few applications exist in urban drainage modelling. This contribution discusses two GSA methods applied to a sewer flow and sewer water quality model: Standardised Regression Coefficients (SRCs) using Monte-Carlo simulation as well as the Morris Screening method. For selected model variables we evaluate how the sensitivities are influenced by the choice of the rainfall event. The aims are to i) compare both methods concerning the similarity of results and their applicability, ii) discuss the implications for factor fixing (identifying non-influential parameters) and factor prioritisation (identifying important parameters) and iii) rank the important parameters for the investigated model. It was shown that both methods lead to similar results for the hydraulic model. Parameter interactions and non-linearity were identified for the water quality model and the parameter ranking differs between the methods. For the investigated model the results allow a sound choice of output variables and rainfall events in view of detailed uncertainty analysis or model calibration. We advocate the simultaneous use of both methods for a first model assessment as they allow answering both factor fixing and factor prioritisation at low computational cost.

Monitoring and modelling to support wastewater system management in developing mega-cities

Urban drainage system models can be useful to assess and manage system performance and to plan its development. However, due to data and computational costs, sophisticated, high-resolution contemporary models of the sewer system may not be applicable. This constraint is particularly marked in developing country mega-cities where catchments can be large, data tend to be scarce, and there are many unknowns, for example regarding sources, losses and wrong connections. This paper presents work undertaken over the last 7 years to develop a suitable monitoring and modelling framework to support operation and development of the wastewater system of Bogotá (Colombia). Components of the framework covered here are: (a) the flow and water quality database, (b) a wastewater pollution load generator, and (c) a semi-distributed sewer network model, which aims at a complexity that matches the information available from the previous two components. Results from a catchment within Bogotá, area 150 km(2) and with 2.5 million inhabitants, show that the model outputs capture the scale and dynamics of the observed concentrations and loads at various points on the sewer system. However uncertainty is high because much of variability of observed dry weather flow profiles is apparently random. Against this variability, the effects of in-sewer processes were not identifiable except where backwaters caused particularly high retention times. Hence the work has resulted in an operational model with a scientifically justified, yet useful, level of complexity for Bogotá. More generally, the work demonstrates the value of monitoring and modelling programmes, including having modellers actively involved in monitoring specification and operations; and the insights into suitable level of model complexity that may be gained by uncertainty and sensitivity analysis.

Integration of freshwater environmental policies and wastewater treatment plant management

In the last decade the political awareness of river water quality issues has grown substantially over the world and legislation is accordingly adapting. In the European Union (EU), two different directives regulate separately the characteristics of the discharged water and the chemical status of the receiving freshwater ecosystem. On the one hand, the characteristics of the urban effluents are regulated by the EU Directive 91/271/EEC, which defines limits on different elements set in the form of both static emission limits and minimum percentage load reductions. On the other hand, the characteristics of the receiving freshwater ecosystems are described in the EU Water Framework Directive (2000/60/EEC), which sets minimum 'good' chemical and ecological status in water bodies that should be achieved by 2015, and aims for an ecosystem-based management. With the support of an example, we show that there is a gap in these EU environmental policies leading to non-integrated management, which may result on adverse environmental and economical consequences. We believe that these policies should be updated and tuned to account for an integrated perspective, allowing a more efficient and sustainable management of wastewater treatment plants, maximizing the ecological, economical and social benefits of the system as a whole.