Performance evaluation of optimization models in the determination of wastewater treatment efficiencies inside watersheds

Abstract

Determination of sewage treatment plants pollutant removal efficiencies, considering the protection of water resources, is very difficult because it involves complex analysis that must take into account multiple discharges into watercourses presenting different self depuration capacities. The research aimed to evaluate different optimization models for determination of minimum sewage treatment efficiencies for plants located in a watershed. The analyzed optimization models involves minimization of the sum of treatment efficiencies and minimization of inequity between sewage treatment efforts. Water quality mathematical model and Genetic Algorithm were combined in a MatLab software computing environment. The Pardo river watershed is the study area. Pardo river is a tributary of the Itapemirim river, important watercourse located in the southern part of Espirito Santo State, in Brazil. The results indicate that the optimization models that incorporate measurement of equity as a problem restriction did not generate consistent answers, probably because of the wide range of sewage loads values considered in the Pardo river watershed. The models that incorporate equity measures in the objective function showed satisfactory performance and resulted in very close values for minimum sewage treatment efficiencies.

Water quality modeling of the São Joaquim stream, Brazil

“…Such fact was attributed to two features of the discharges: high organic matter concentration, which is aerobically decomposed; and low DO concentration. The influence of the high organic matter concentration, resulting from domestic wastewater, on the reduction of DO concentrations was observed by Santoro et al (2016) and Mateus et al (2015).…”

Wastewater treatment systems selection inside watersheds by using multiobjective analysis

“…The water flow and quality conditions immediately prior to receiving sewage had a direct influence on the estimated treatment efficiencies, as sought by the objective function established (Table 4), required very distinct treatment efficiencies (90.0 and 27.9%, respectively), since Pardo river assimilation capacity at the Iúna sewage discharge point was considerably higher than that of the same watercourse when receiving Ibatiba discharge. It should be noted that in Santoro, Reis and Mendonça (2016) work -whose optimization models did not consider the condition of the recipient bodies immediately upstream raw domestic sewage inputs -the estimated treatment efficiency for Iúna reached 94%.…”

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

“…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.…”