Scenario analysis for the role of sanitation infrastructures in integrated urban wastewater management

Devesa, F.; Comas, Joaquím; Turon, Clàudia; Freixó, Angel; Carrasco, F.; Poch, M.

doi:10.1016/j.envsoft.2008.08.003

Cited by 37 publications

(15 citation statements)

References 25 publications

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“…Devesa et al [9] present an integrated model for the management of sanitation infrastructures based on Infoworks WS, GPS-X (software simulator for WWTPs), and Infoworks RS.…”

Section: Dss For the Wrm Based On Quality Criteriamentioning

confidence: 99%

Decision Support Systems for Integrated Water Resources Management Under Water Scarcity

Comas

Poch

2009

The Handbook of Environmental Chemistry

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Environmental decision support systems (EDSS) can be defined as intelligent information systems that are able to integrate numerical models (linear or nonlinear) with artificial intelligence (AI) techniques, together with geographical information and environmental ontologies. EDSS emulate the expert's reasoning processes in decision making, integrating geographical information and environmental ontologies, reducing the time in which decisions are made, as well as improving the consistency and quality of those decisions. EDSS can be useful to cope with the complexity and multidisciplinary nature of Integrated Water Resource Management (IWRM). Besides, the Drought Management Plan Report written by the Water Scarcity and Droughts Expert Network (November 2007) states the "Development of decision support systems for the best exploitation of all information available, including drought forecasts, in order to optimize drought management and mitigation measures" as one of the main needs for advances in drought research. The necessity to confront complexity when dealing with IWRM is first stated in the paper. Then an EDSS as a promising tool to cope with this complexity is introduced, putting special emphasis in a proposal for EDSS development. Next the paper reviews the more relevant decision support systems (DSS) published for IWRM under water scarcity. Classical DSS to model environmental systems as well as those DSS including knowledge-based or AI techniques (i.e., EDSS) are reviewed. Open questions related to the EDSS development and application include improvement of data and knowledge acquisition and knowledge implementation methods, better integration of numerical models and AI techniques (both in simulation and real applications), evaluation of EDSS (lack of benchmarks), protocols to facilitate sharing and reuse of knowledge, involvement of end-users, and probably others.

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“…Devesa et al [9] present an integrated model for the management of sanitation infrastructures based on Infoworks WS, GPS-X (software simulator for WWTPs), and Infoworks RS.…”

Section: Dss For the Wrm Based On Quality Criteriamentioning

confidence: 99%

Decision Support Systems for Integrated Water Resources Management Under Water Scarcity

Comas

Poch

2009

The Handbook of Environmental Chemistry

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“…The WaWO+ was built because previous research in the field (e.g. [29], [8], [10], [48]) has encouraged us to use more sophisticated techniques in knowledge representation and management due to the number of actors, the large quantity of variables and the complexity of the different processes involved in reasoning about wastewater treatment UWS in RB s, in particular in the Besòs Basin.…”

Section: Discussionmentioning

confidence: 99%

“…In these studies, the elements under consideration were blocks of the UWSs as follows: the sewer system, the WWTPs and, the river itself [8], [29], [54]. Here, we are targeting a more ambitious goal.…”

Section: The River Basinmentioning

confidence: 99%

Reasoning about river basins: WaWO+ revisited

Oliva-Felipe

Gómez-Sebastià

Verdaguer

et al. 2017

Environmental Modelling & Software

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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.

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“…Industrial contributions are usually highly variable in volume and composition, and these variations are not easily foreseeable Muñoz et al 2013). Environmental concerns regarding UWS operation are extremely important, as effluents may alter the characteristics of the receiving waters (Corominas et al 2013;Devesa et al 2009;Estrada et al 2011;Hernandez and Uddameri 2013;Hosomi 2014;Ling et al 2014;Verdaguer et al 2014). Therefore, management systems must address a high level of complexity due to uncertain influent compositions (Shen et al 2008;Xu and Qin 2013).…”

Section: Introductionmentioning

confidence: 98%

An exact approach for the prioritization process of industrial influents in wastewater systems

Verdaguer

Suy

Villaret

et al. 2015

Clean Techn Environ Policy

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In wastewater systems, the efficiency of the treatment process is strongly related to the composition of its influent. When the treatment is overloaded (in volume and/or pollutants), its efficiency decreases and the effluent cannot attain the quality required by the receiving waters. This work considers the problem of mixing multiple wastewater streams, with multiple contaminants, into a single stream (the influent) on which various specifications are imposed. The problem has recently been solved by probabilistic methods that can achieve a nearly optimal solution. In this paper, an exact technique is proposed to find the optimal solution with a mixed-integer linear programming solver for the first time. The procedure is applied to a case study with different industrial effluents whose discharges will compose the influent to a treatment plant with constrained capacity (both in volume and pollutant loads). The optimal utility solution achieved describes the discharges that satisfy all constraints. This proposal constitutes an efficient way to manage treatment influents while reducing the computational time required by two orders of magnitude compared to probabilistic methods.

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Scenario analysis for the role of sanitation infrastructures in integrated urban wastewater management

Cited by 37 publications

References 25 publications

Decision Support Systems for Integrated Water Resources Management Under Water Scarcity

Decision Support Systems for Integrated Water Resources Management Under Water Scarcity

Reasoning about river basins: WaWO+ revisited

An exact approach for the prioritization process of industrial influents in wastewater systems

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