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In the context of climate change and increasing water scarcity, adopting water demand-side management (DSM) policies has become necessary. This study advocates for utilizing agent-based modelling (ABM) as a robust simulation tool to assess the impact of nonprice (nudges) and price (changes in increasing block tariff) measures on urban water use. Overcoming challenges posed by insufficient high-quality data, the research integrates four sociocognitive profiles and diverse household income levels to reflect the variability in DSM policy effectiveness based on socioeconomic characteristics. Through 125 simulated scenarios combining various increasing block tariffs with nonpricing measures, the study reveals an average monthly demand reduction ranging from 8.1% to 15.6%. Significantly, nonprice measures prove more effective in curbing water use than pricing measures, attributed to the prioritization of environmental concerns in conservation efforts. Higher-income households exhibit less-pronounced reductions in water consumption. Emphasizing the reliability of ABM for ex ante evaluations of DSM policies, this research underscores the importance of a balanced approach, incorporating both nonprice and price-based measures, to effectively address water scarcity challenges., Pol Vidal-Lamolla acknowledges support from the LEQUIA Research Group, Aigües de Barcelona and the Industrial Doctorate Programme of the Catalan Agency for Management of University and Research Grants (AGAUR), Spain (Ref 2021 DI 85). LEQUIA has been recognized as a consolidated research group by AGAUR (Ref 2021 SGR 1352)., Peer Reviewed, Postprint (published version)

The development and application of new forms of automation and monitoring, data mining, and the use of AI data sources and knowledge management tools in the water sector has been compared to a ‘digital revolution’. The state-of-the-art literature has analysed this transformation from predominantly technical and positive perspectives, emphasising the benefits of digitalisation in the water sector. Meanwhile, there is a conspicuous lack of critical literature on this topic. To bridge this gap, the paper advances a critical overview of the state-of-the art scholarship on water digitalisation, looking at the sociopolitical and ethical concerns these technologies generate. We did this by analysing relevant AI applications at each of the three levels of the UWC: technical, operational, and sociopolitical. By drawing on the precepts of urban political ecology, we propose a hydrosocial approach to the so-called ‘digital water ‘, which aims to overcome the one-sidedness of the technocratic and/or positive approaches to this issue. Thus, the contribution of this article is a new theoretical framework which can be operationalised in order to analyse the ethical–political implications of the deployment of AI in urban water management. From the overview of opportunities and concerns presented in this paper, it emerges that a hydrosocial approach to digital water management is timely and necessary. The proposed framework envisions AI as a force in the service of the human right to water, the implementation of which needs to be (1) critical, in that it takes into consideration gender, race, class, and other sources of discrimination and orients algorithms according to key principles and values; (2) democratic and participatory, i.e., it combines a concern for efficiency with sensitivity to issues of fairness or justice; and (3) interdisciplinary, meaning that it integrates social sciences and natural sciences from the outset in all applications., Peer Reviewed, Postprint (published version)

Anaerobic digestion (AnD) is a process that allows the conversion of organic waste into a source of energy such as biogas, introducing sustainability and circular economy in waste treatment. AnD is an intricate process because of multiple parameters involved, and its complexity increases when the wastes are from different types of generators. In this case, a key point to achieve good performance is optimisation methods. Currently, many tools have been developed to optimise a single AnD plant. However, the study of a network of AnD plants and multiple waste generators, all in different locations, remains unexplored. This novel approach requires the use of optimisation methodologies with the capacity to deal with a highly complex combinatorial problem. This paper proposes and compares the use of three evolutionary algorithms: ant colony optimisation (ACO), genetic algorithm (GA) and particle swarm optimisation (PSO), which are especially suited for this type of application. The algorithms successfully solve the problem, using an objective function that includes terms related to quality and logistics. Their application to a real case study in Catalonia (Spain) shows their usefulness (ACO and GA to achieve maximum biogas production and PSO for safer operation conditions) for AnD facilities., Peer Reviewed, Postprint (published version)

Water managers have to deal with complex problems due to the intertwined characteristics of processes, in particular those that occur in wastewater systems. Existing modelling approaches are usually centred in the physical, chemical and biological aspects of the individual processes, excluding the social and organisational context that will generate the global behaviour. These also include the responsibilities and decision making of different actors in the system. This paper proposes an agent-based model with the novelty to integrate the social and organisational structure of the wastewater system from which emerges the global behaviour of the system. The modelling process allows considering the legal regulations and the technical limits that would drive the decision making. The instantiation of the model, implementing a small system, evidenced the usefulness of this approach to manage the complexity of wastewater systems and its possible contribution to prevent environmental problems., LEQUIA has been recognised as consolidated research group by the Catalan Government with code 2017-SGR-1552. KEMLg@IDEAI is part of a research group, recognised as consolidated research group by the Catalan Government with code 2017-SGR-574., Peer Reviewed, Postprint (published version)

Co-digestion is a well-established strategy to maximise the capacity of anaerobic digestion in wastewater treatment plants (WWTPs). Many tools have been developed to optimise the blend composition. However, the logistics associated with each component of the blend remain a relatively unexplored field, which can yield significant planning challenges. In this paper, an ant colony optimisation based approach is proposed to address these challenges. The proposed algorithm maximises an objective function composed of a first term related to the quality of the sludge and a second term related to the distance between the sludge generator and the anaerobic co-digester. The algorithm successfully optimises the blend composition by considering the related logistics, achieving an optimum blend with an approximately 18% volume of co-substrate. The approach presented here has been used to plan co-digestion using real data from an actual sanitation network composed of 13 WWTPs in the area of the Besos river basin in Catalonia, and an optimised co-digestion planning strategy with a waste management cost reduction of 77% was obtained, Peer Reviewed, Postprint (author's final draft)

In this work, a decision support system (DSS) coupled with wastewater treatment plant (WWTP) simulator tool that uses a hierarchical set of key performance indicators (KPIs) to provide an assessment of the performance of WWTP systems is presented. An assessment of different Scenarios in a real WWTP case study, each consisting of a different set of sludge line technologies and derived combinations, was successfully conducted with the developed DSS–WWTP simulator, based on Scenario simulation and hierarchical KPI analysis. The test carried out on the selected WWTP showed that although thermal valorisation and thermal hydrolysis showed similar (the best) economic viability, the latter showed additional benefits, including synergies related to improving the thermal balance of the overall WWTP even when considering other technologies. On the other hand, biogas-upgrading technologies allowed reduction of emissions, but with higher costs and thermal demands. The usage of this tool may allow the development of proposals for technological priorities as a pathway to the transition to circular economy based on the management criteria of the correspondent sanitation system., This work is supported by DAM (Depuración de Aguas del Mediterráneo) and by the Industrial Doctorate Programme (ref. 2017-DI-048) of the Catalan Agency of University and Research Grants Management (AGAUR)., Peer Reviewed, Postprint (published version)

The so-called fourth revolution in the water sector will encounter the Big data and Artificial Intelligence (AI) revolution. The current data surplus stemming from all types of devices together with the relentless increase in computer capacity is revolutionizing almost all existing sectors, and the water sector will not be an exception. Combining the power of Big data analytics (including AI) with existing and future urban water infrastructure represents a significant untapped opportunity for the operation, maintenance, and rehabilitation of urban water infrastructure to achieve economic and environmental sustainability. However, such progress may catalyze socio-economic changes and cross sector boundaries (e.g., water service, health, business) as the appearance of new needs and business models will influence the job market. Such progress will impact the academic sector as new forms of research based on large amounts of data will be possible, and new research needs will be requested by the technology industrial sector. Research and development enabling new technological approaches and more effective management strategies are needed to ensure that the emerging framework for the water sector will meet future societal needs. The feature further elucidates the complexities and possibilities associated with such collaborations., Manel Garrido-Baserba and Diego Rosso acknowledge the United States Department of Energy (CERC-WET US Project 525 2.5). Lluís Corominas acknowledges the Ministry of Economy and competitiveness for the Ramon and Cajal grant (RYC2013-465 14595) and the following I3. We thank Generalitat de Catalunya through Consolidated Research Group 2017 SGR 1318. ICRA researchers acknowledge funding from the CERCA program., Peer Reviewed, Postprint (author's final draft)

This paper examines wastewater treatment and reuse in Catalonia and Valencia through a benchmarking analysis of energy intensities of wastewater treatment plants (WWTPs) located in the coastal municipalities of both regions also involving comparison with average European data on energy use by these plants. The comparison of European and Spanish Mediterranean WWTPs indicates that small Mediterranean plants are less energy intensive than their European counterparts, while for larger plants (above 10,000 m3 /day) the reverse is true. As to the comparison between Catalan and Valencian plants, the latter are generally smaller than the former, and also slightly more energy intensive. Regarding reuse, the geographical context would explain these differences in terms of the final destination of effluents treated in these plants. The important presence of irrigated agriculture in Valencia is responsible for the reuse of 45% of potentially reclaimed water while Catalonia, with a different socioterritorial reality, reuses less than 3% of the total effluent treated., El contexto geográfico del tratamiento y reutilización de aguas residuales: un análisis benchmarking para el litoral mediterráneo españolEste artículo examina los tratamientos y la reutilización de las aguas residuales en Cataluña y Valencia a través de un análisis comparativo (benchmarking) de las intensidades energéticas de todas las plantas de tratamiento de aguas residuales (EDAR) ubicadas en los municipios costeros de ambas regiones, que también se comparan con los promedios europeos. La comparación de las EDAR mediterráneas europeas y españolas indica que la plantas mediterráneas más pequeñas son más eficientes energéticamente que sus equivalentes europeas, mientras que para las plantas grandes (más de 10 000 m3/día) se da el caso contrario. En cuanto a la comparación entre plantas catalanas y valencianas, estas últimas son generalmente más pequeñas que las primeras y un poco menos eficientes energéticamente. El contexto geográfico puede explicar estas diferencias en términos del destino final de los efluentes tratados en estas plantas. La gran presencia de la agricultura de regadío en Valencia es responsable de la reutilización del 45 % de las aguas residuales tratadas, mientras que Cataluña, al carecer de esta alternativa, reutiliza menos del 3 %, aunque se están explorando iniciativas de reutilización indirecta para usos potables.

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0, This paper characterizes part of an interdisciplinary research effort on Artificial Intelligence (AI) techniques and tools applied to Environmental Decision-Support Systems (EDSS). WaWO+ the ontology we present here, provides a set of concepts that are queried, advertised and used to support reasoning about and the management of urban water resources in complex scenarios as a River Basin. The goal of this research is to increase efficiency in Data and Knowledge interoperability and data integration among heterogeneous environmental data sources (e.g., software agents) using an explicit, machine understandable ontology to facilitate urban water resources management within a River Basin., Peer Reviewed, Postprint (author's final draft)

Environmental decision support systems (EDSSs) are attractive tools to cope with the complexity of environmental global challenges. Several thoughtful reviews have analyzed EDSSs to identify the key challenges and best practices for their development. One of the major criticisms is that a wide and generalized use of deployed EDSSs has not been observed. The paper briefly describes and compares four case studies of EDSSs applied to the water domain, where the key aspects involved in the initial conception and the use and transfer evolution that determine the final success or failure of these tools (i.e., market uptake) are identified. Those aspects that contribute to bridging the gap between the EDSS science and the EDSS market are highlighted in the manuscript. Experience suggests that the construction of a successful EDSS should focus significant efforts on crossing the death-valley toward a general use implementation by society (the market) rather than on development., The authors would like to thank the Catalan Water Agency (Agència Catalana de l’Aigua), Besòs River Basin Regional Administration (Consorci per la Defensa de la Conca del Riu Besòs), SISLtech, and Spanish Ministry of Science and Innovation for providing funding (CTM2012-38314-C02-01 and CTM2015-66892-R). LEQUIA, KEMLG, and ICRA were recognized as consolidated research groups by the Catalan Government under the codes 2014-SGR-1168, 2013-SGR-1304 and 2014-SGR-291., Peer Reviewed, Postprint (published version)

Wastewater management is a complex task involving a wide range of technical environmental and social factors. Furthermore, it typically requires the coordination of a heterogeneous society of actors with different goals. Regulations and protocols can be effectively used to tackle this complexity. In this chapter we present a norm-aware multi-agent system for social simulations in a river basin. The norms we present are inspired in European policies for wastewater management and they can evolve through time., Peer Reviewed, Postprint (author's final draft)

The use of Horizontal Subsurface Constructed Wetlands (HSCWs) for treating wastewaters in small communities has increased in the last years due to HSCW’s ecological singularities. Unfortunately, the same singularities that differentiate HSCWs complicate any attempt to develop models and produce generic decision-support systems for them. Classical mathematical and statistical approaches used in other Wastewater Treatment Plants do not properly fit the particularities of HSCW and provide little insight in the domain of HSCW. We introduce a novel approach based on logic-based declarative specifications, i.e. non-monotonic causal logic, to capture explicit and implicit knowledge about HSCWs. By expressing all the relevant aspects of a HSCW in a declarative way, we produce a logic-based model which captures features that other approaches fail to formalize. At the end, we produce a complete decision-support system based on that model and test it against a set of realistic scenarios validated by experts. We discuss in which aspects this approach performs better than the most commonly proposed solutions in the bibliography and why it does so., Peer Reviewed, Postprint (published version)

“Water is a scarce resource and its management has to be as effective as possible”. Most of us would certainly agree with this fine sounding phrase. But developing it and putting it into practice is not easy. Firstly, because we are already having problems identifying the meaning or interpretation we give to some words. For example, water as a resource. Water is not just a natural resource, it is the basis of the industrial sector, a generator of cultural heritage and a linchpin of society. And we sometimes use the term scarce when referring to a problem of distribution or overexploitation. In any case, this means that water management is very complex. This is because there are different agents involved and all of them have different interests; these interests are often contradictory and can lead to conflict. Everyone understands the concept of efficient management differently. Efficient: why and for whom? At the same time, we have to make decisions. Decisions that involve a way of managing the resource. For example, authorising (or not) a withdrawal from a water course, building (and how) a treatment plant or defining (what and in which range) the quality parameters guaranteeing its drinkability... These examples, and many more that we could cite, are some of the aspects on which a group of people are responsible for acting, deciding and getting the decisions implemented. The hypothesis presented in this book is that to achieve this efficient management there are no simple formulas or universal solutions. However, this does not mean that all solutions are equally correct. Experience shows us that some are better than others., Postprint (published version)

Daily operation and maintenance tasks are needed to guarantee the correct performance of constructed wetlands. The definition of these activities is a complex task since these actions vary according to the characteristics of each facility. To support the definition of these operation and maintenance protocols an Environmental Decision Support System (EDSS) has been constructed (EDSS-maintenance). The methodology used to develop EDSS-maintenance is based on the following five steps: environmental problem analysis, data and knowledge acquisition, model selection, model implementation and evaluation process. The first four steps have been finished; however, the evaluation process is ongoing. This document presents a new approach for this step: two numerical indices allow (a) verifying the performance of the EDSS-maintenance and (b) validating the compliance of the protocols with the user requirements. Moreover, another index enables an easy revision and improvement of the knowledge bases (problems, causes and actions) and so enhances the decision support system., Postprint (published version)

Wastewater Treatment Plants (WWTPs) control and prediction under a wide range of operating conditions is an important goal in order to avoid breaking of environmental balance, keeping the system in stable operating conditions and suitable decision-making. In this respect, the availability of models characterizing WWTP behaviour as a dynamic system is a necessary first step. However, due to the high complexity of the WWTP processes and the heterogeneity, incompleteness and imprecision of WWTP data, and finding suitable models poses substantial problems. In this work, an approach via soft computing techniques is sought, in particular, by experimenting with fuzzy heterogeneous time-delay neural networks to characterize the time variation of outgoing variables. Experimental results show that these networks are able to characterize WWTP behaviour in a statistically satisfactory sense and also that they perform better than other well-established neural network models., Peer Reviewed, Postprint (author's final draft)

Wastewater Treatment Plants (WWTPs) control and prediction under a wide range of operating conditions is an important goal in order to avoid breaking of environmental balance, keep the system in stable operating conditions and suitable decision-making. In this respect, the availability of models characterizing WWTP behaviour as a dynamic system, is a necessary first step. However, due to the high complexity of the WWTP processes and the heterogeneity, incompleteness and imprecision of WWTP data, finding suitable models poses substantial problems. In this paper, an approach via soft computing techniques is sought, in particular, by experimenting with fuzzy heterogeneous time-delay neural networks to characterize the time variation of outgoing variables. Experimental results show that these networks are able to characterize WWTP behaviour in a statistically satisfactory sense and also that they perform better than other well-established neural network mode., Peer Reviewed, Postprint (published version)