Proposal of a methodology for pre-selection of sewage treatment systems within watersheds

Abstract

The selection of sewage treatment plants within watersheds is a complex process when there are multiple outflows presenting different loads and watercourses presenting different assimilation capabilities. In this context, the present study aims to establish a methodology for pre-selection of wastewater treatment alternatives within watersheds. The methodology involves the combined use of water quality model, optimization technique and a set of technical and economic criteria associated with different wastewater treatment systems. To evaluate the proposed methodology there were considered different effluent disposal scenarios in the Pardo river watershed. Pardo is a major tributary of the Itapemirim river, watercourse located in the southern portion of Espírito Santo State, Brazil. The results indicated that the optimization model, that aimed to minimize wastewater treatment efficiencies within the watershed, considering watercourses self-purification capacities, selected treatment systems ranging from the combination of UASB and polishing lagoons systems to slow infiltration, treatment alternatives that presented the lowest net cost estimates. The incorporation of equity perspective between treatment systems increased the total present net cost associated with wastewater treatment within the watershed.Keywords: Water quality model; Optimization; Genetic algorithm; Wastewater treatment. RESUMOO processo de seleção de uma estação de tratamento de esgoto é complexo quando observado do ponto de vista de uma bacia hidrográfica, onde existem múltiplos lançamentos apresentando diferentes cargas e corpos d'água com diferentes capacidades de assimilação. Neste contexto, a presente pesquisa tem como objetivo estabelecer metodologia para a pré-seleção de alternativas de tratamento de esgoto no âmbito de bacias hidrográficas. A proposta metodológica envolve o uso combinado de modelo de qualidade de água, técnica de otimização e um conjunto de critérios de natureza técnica e econômica associados aos diferentes sistemas de tratamento de esgotos. Para avaliação da metodologia proposta foram considerados diferentes cenários de disposição de efluentes na bacia hidrográfica do rio Pardo, importante afluente do rio Itapemirim, curso d'água da porção sul do estado do Espírito Santo. Os resultados indicaram que o modelo de otimização que buscou a minimização das eficiências de tratamento no âmbito da bacia, permitindo uso da capacidade e de autodepuração dos cursos d'água, selecionou sistemas de tratamento que variaram da combinação de reatores UASB e lagoas de polimento a sistemas de infiltração lenta, alternativas de tratamento que apresentaram menores estimativas de custos presentes líquidos. A incorporação da equidade entre os sistemas de tratamento aumentou significativamente os custos presentes líquidos totais associados ao tratamento de esgoto no âmbito da bacia hidrográfica.Palavras-chave: Modelo de qualidade de água; Otimização; Algoritmo genético; Tratamento de esgotos.RBRH, Porto Alegre, v. 22, e12, 2017Proposal o...

Sewage treatment efficiencies estimation for urban areas located in the River Pardo’s watershed by associating nonlinear programming and water quality modeling

“…The results achieved in the present study are similar to those found in Santoro, , Fantin, Reis and Mendonça (2017), and Bringer (2017), who used GA as an optimization tool to determine minimum sewage treatment efficiencies for the river Pardo's watershed. In this context, NLP has produced consistent and similar results to those obtained from the use of a metaheuristic optimization technique, which usually requires higher computational demands.…”

“…In this context, the association between water quality models and optimization techniques can allow the determination of the optimal treatment efficiencies combination to be adopted within a watershed (ANDRADE; MAURI; MENDONÇA, 2013). In this research line, different studies (VALORY et al, 2013;MANSHADI;NIKSOKHAN;ARDESTANI, 2015;SANTORO;MENDONÇA, 2016;FANTIN;MENDONÇA, 2017;BRINGER;MEN-DONÇA, 2018;AGHASIAN et al, 2019;SÁ et al, 2019) have prioritized the association between water quality models and Genetic Algorithm (GA) metaheuristic optimization technique. According to Lacerda and Carvalho (1999), GAs have been employed in complicated problems (where other optimization methods fail) and have several advantages, such as the possibility to work both with continuous and discrete parameters (or a combination of them), several optimization variables, and complex optimization functions.…”

Scenarios of water quality management in watershed with distributed spatio-temporal simulation

“…The concentration permanence curve represents the frequency that its values are not exceeded (Cunha et al, 2011). This study sought to analyse the water quality from pollutant concentrations, differing from other studies that analyse the quality of the resulting loads in the water courses (Lima et al, 2018;Fantin et al, 2017;Salla et al, 2013;Teodoro et al, 2013). This analysis is more complete by virtue of assigning the simultaneous flow to each analysed moment, bringing more reality to the presented results.…”

“…Bitencourt (2018) reported that most works for framing water courses in Brazil use one-dimensional models of steady states. One-dimensional models, such as QUAL2E, QUAL2K and QUAL-UFMG, are used to generate current and future water quality scenarios for water courses (Lima et al, 2018;Fantin et al, 2017;Calmon et al, 2016;Salla et al, 2013;Teodoro et al, 2013;Silva, 2016;Noh et al, 2015;Babbar, 2014;Wu & Fan, 2017;Korf et al, 2017). However, it should be considered that different flow rates influence water quality behaviour, as demonstrated by Brites (2010), Ferreira et al (2016) and Calmon et al (2016).…”

Wastewater treatment systems selection inside watersheds by using multiobjective analysis

“…On the other hand, Nikoo, Kerachian and Niksokhan (2012), Mahjouri and Bizhani-Manzar (2013), Cho and Lee (2014), Lei et al (2015), Ashtiani, Niksokhan and Jamshidi (2015), Nikoo, Beiglou and Mahjouri (2016), Valory, Reis and Mendonça (2016) and Fantin, Reis and Mendonça (2017) works, in addition to minimizing treatment costs, incorporated into the wastewater management problem the "Polluter Pays Principle", which, in turn, expresses the notion that as greater the responsibility for pollution, greater should be the amount paid by the polluter. Thus, these studies considered costs distribution fairness principles, either in the search for water courses self-purification capacities adequate apportionment, or in the search for adequate costs distribution, also through water quality modeling and optimization techniques.…”