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Planning solutions for wastewater system problems are often sought at a local level-that is, each city develops its own solution. However, in many cases, it would be possible to find solutions that are better both from the economic and the environmental viewpoints if they were looked for at a regional level. In this article, we present an efficient simulated annealing (SA) algorithm for solving a regional wastewater system planning model. The model is aimed at determining the minimum-cost configuration for the system that will drain the wastewater generated by the population centers of a region, while complying with all relevant regulations. In particular, the system must ensure that the wastewater discharged from each treatment plant will not exceed a given maximum amount, consistent with the water quality standards defined for the receiving water body. The SA algorithm is termed efficient because its parameters were calibrated to ensure optimum or near-optimum solutions to the model within reasonable computing time. The calibration was performed using a particle swarm algorithm for a large set of test instances designed to replicate real-world problems.

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9Regional wastewater systems are used for the collection and treatment of the wastewater 10 generated in a region, and aimed at guaranteeing surface water quality. The volumes of 11 wastewater to process depend on future population, and thus are affected by the 12 uncertainty inherent to population dynamics. In this article, we present a robust 13 approach to the planning of regional wastewater systems under population dynamics 14 uncertainty. The approach searches for the optimal configuration of the sewer networks 15 and for the best location, type, and size of the possible pump stations and treatment 16 plants to include in the system. It assumes uncertainty to be described by a given 17 number of discrete scenarios of known probabilities, and relies on discrete nonlinear 18 optimization models whose objective is to minimize the expected regret of solutions 19 with respect to total costs. As demonstrated through a case study developed for the 20 North Baixo Mondego area, in central Portugal, the results obtained through the 21 proposed approach provide clear insights into the wastewater system planning decisions 22 to make and do not require excessive computational effort. 23 Keywords 24Wastewater systems, population projections, robust optimization, simulated annealing 25 26

Climate change and urbanization are the main factors involved in increasing cities' susceptibility to flood events. Extreme rainfall events are occurring more often due to climate change and this, together with the effect of impermeable surfaces, means that the runoff increases. Consequently, the existing stormwater drainage systems need to be adapted. One solution to adapt these systems would be to include infrastructure elements, such as storage units, in the hydraulic network to control flow and reduce peak flows. This paper presents a decision support model for the optimal siting and sizing of storage units with flow control in existing urban stormwater systems where flood events are frequent. Direct flood damage will be taken into account in the decision process, and thus the cost of construction and maintenance of storage units will be considered along with the cost of flood damage, in the determination of the solution to be implemented. This damage relates to losses in the affected areas and depend on the land use type (e.g. uses of buildings) and on the flood depth affecting it. A computer program, OptSU, was developed to implement the model. It includes a resolution method based on a simulated annealing algorithm that calls upon a hydraulic simulator whenever necessary. The optimization model is then tested on a case study inspired by a real urban stormwater system in Portugal.

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