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On-line continuous monitoring of water bodies produces large quantities of high frequency data. Long-term quality control and applicability of these data require rigorous storage and documentation. To carry out these activities successfully, a database has to be built. Such a database should provide the simplicity to store and document all relevant data and should be easy to use for further data evaluation and interpretation. In this paper, a comprehensive database structure for water quality data is proposed. Its goal is to centralize the data, standardize their format, provide easy access, and, especially, document all relevant information (metadata) associated with the measurements in an efficient way. The emphasis on data documentation enables the provision of detailed information not only on the history of the measurements (e.g., where, how, when and by whom was the value measured) but also on the history of the equipment (e.g., sensor maintenance, calibration/validation history), personnel (e.g., experience), projects, sampling sites, etc. As such, the proposed database structure provides a robust and efficient tool for functional data storage and access, allowing future use of data collected at great expense. [ABSTRACT FROM AUTHOR]

The Water Poverty Index (WPI) has been recognized as a useful tool in policy analysis. The index integrates various physical, social and environmental aspects to enable more holistic assessment of water resources. However, soundness of this tool relies on two complementary aspects: (i) inadequate techniques employed in index construction would produce unreliable results, and (ii) poor dissemination of final outcome would reduce applicability of the index to influence policy-making. From a methodological point of view, a revised alternative to calculate the index was developed in a previous study. This paper is therefore concerned not with the method employed in index construction, but with how the composite can be applied to support decision-making processes. In particular, the paper examines different approaches to exploit the index as a policy tool. A number of alternatives to disseminate achieved results are presented. The implications of applying the composite at different spatial scales are highlighted. Turkana District, in Kenya has been selected as initial case study to test the applicability and validity of the index. The paper concludes that the WPI approach provides a relevant tool for guiding appropriate action and policy-making towards more equitable allocation of water resources. [ABSTRACT FROM AUTHOR]

Digital Twins (DTs) are on the rise as innovative, powerful technologies to harness the power of digitalisation in the WRRF sector. The lack of consensus and understanding when it comes to the definition, perceived benefits and technological needs of DTs is hampering their widespread development and application. Transitioning from traditional WRRF modelling practice into DT applications raises a number of important questions: When is a model's predictive power acceptable for a DT? Which modelling frameworks are most suited for DT applications? Which data structures are needed to efficiently feed data to a DT? How do we keep the DT up to date and relevant? Who will be the main users of DTs and how to get them involved? How do DTs push the water sector to evolve? This paper provides an overview of the state-of-the-art, challenges, good practices, development needs and transformative capacity of DTs for WRRF applications. HIGHLIGHTS A Digital Twin distinguishes itself from a simulation model by a continuous, automated data connection.; Current DT projects in WRRFs focus on operational support and control.; Combining mechanistic models and data-driven techniques into hybrid models can accelerate the adoption of DTs.; Data and information models are key for the implementation and upscaling of DTs.; WRRF staff should be included during the development stages of DTs.;

The lack of appropriate data management tools is presently a limiting factor for a broader implementation and a more efficient use of sensors and analysers, monitoring systems and process controllers in wastewater treatment plants (WWTPs). This paper presents a technical solution for advanced data management of a full-scale WWTP. The solution is based on an efficient and intelligent use of the plant data by a standard centralisation of the heterogeneous data acquired from different sources, effective data processing to extract adequate information, and a straightforward connection to other emerging tools focused on the operational optimisation of the plant such as advanced monitoring and control or dynamic simulators. A pilot study of the advanced data manager tool was designed and implemented in the Galindo-Bilbao WWTP. The results of the pilot study showed its potential for agile and intelligent plant data management by generating new enriched information combining data from different plant sources, facilitating the connection of operational support systems, and developing automatic plots and trends of simulated results and actual data for plant performance and diagnosis. [ABSTRACT FROM AUTHOR]