Urban water networks (UWNs) comprise drinking water distribution and urban drainage systems (WDS and UDS). The former are responsible for supplying drinking water to cities and the latter for evacuating wastewater and stormwater runoff. These infrastructures are a fundamental part of the city and are directly linked to its development (Brown et al., 2009). Each of these systems faces challenges to improve and maintain quality service in a dynamic urban environment under a widening range of climatic conditions; especially, in a climate-changing situation. Designing, optimizing, and intervening in these systems requires approximating their hydraulic behavior. Many models have been developed in the past years for simulating UWNs, for example, SOBEK (Deltares, n.d.), WaterCAD (Bentley®, n.d.), EPA-SWMM (Rossman, 2010), among others. Traditional modeling approaches are either based on accurate description of the physical processes (e.g., EPANET;Rossman et al., 2000) or rely on simplified conceptual models (e.g., SIMPOL;Dempsey et al., 1997); nonetheless, the former usually entail computationally expensive calculations while the latter lack fidelity, that is, level of detail. Applications such as optimization, real-time modeling, and uncertainty analysis need efficient models for evaluating the performance

The potential application of Water Hyacinth (Eichhornia crassipes) in organic matter degradation, sedimentation, nutrient and heavy metal absorption and sulfur reduction in the Muña Reservoir has been tested in experimental lagoons. The lagoons were operated at hydraulic retention times (HRT) of 6, 9 and 15 days. One lagoon was covered with Water Hyacinth, which is naturally growing in the Muña Reservoir, while another lagoon was operated as a conventional oxidation pond. The Water Hyacinth lagoon had better removal efficiencies for almost all parameters measured: BOD5, total suspended solids, COD, nitrogen, phosphorus and heavy metals. The oxidation lagoon was facultative for HRT of 9 and 15 days, and anoxic when operated at 6 days HRT. At HRT of 15 days the water quality in the effluent of the covered lagoon corresponded to 12 mg/l of BOD, 6 mg/l of suspended solids and 0.8 mg/l of hydrogen sulfide. Hydrogen sulfide levels in the Muña reservoir can be substantially reduced at HRT higher than 15 days in both lagoons. The uncovered lagoon had better hydrogen sulfide removal during the day but presents high levels at night. If the hydraulic retention time in the Muña reservoir is increased, the water quality of the Bogota river can be substantially improved for all the HRTs tested in the pilot units. HRT seems to give a better prediction of overall effluent water quality than surface loading. More research is needed in order to define the optimum water hyacinth density in the Muña reservoir to determine its influence on the water quality of the effluent. The influence is expected to be negative due to an internal increase of BOD, solids, nutrients and metals loads due to plant decay.

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The optimization of water distribution networks (WDN) has evolved, requiring approaches that seek to reduce capital costs and maximize the reliability of the system simultaneously. Hence, several evolutionary algorithms, such as the non-dominated sorting-based multi-objective evolutionary algorithm (NSGA-II), have been widely used despite the high computational costs required to achieve an acceptable solution. Alternatively, energy-based methods have been used to reach near-optimal solutions with reduced computational requirements. This paper presents a method to combine the domain knowledge given by energy-based methods with an evolutionary algorithm, in a way that improves the convergence rate and reduces the overall computational requirements to find near-optimal Pareto fronts (PFs). This method is divided into three steps: parameters calibration, preprocessing of the optimal power use surface (OPUS) results, and periodic feedback using OPUS in NSGA II. The method was tested in four benchmark networks with different characteristics, seeking to minimize the costs of the WDN and maximizing its reliability. Then the results were compared with a generic implementation of NSGA-II, and the performance and quality of the solutions were evaluated using two metrics: hypervolume (HV) and modified inverted generational distance (IGD+). The results showed that the feedback procedure increases the efficiency of the algorithm, particularly the first time the algorithm is retrofitted.

A model has been developed for the digestion of organic matter in facultative ponds in tropical regions. Complete mixing has been assumed for the aerobic and anaerobic compartments. Settling, aerobic layer oxidation, and anaerobic layer methanogenesis are the main processes for organic matter removal in the water column. Exchange processes between layers are dispersive or soluble exchange, solubilization and transport of organic matter from sediments to water column are also taken into account. Degradation of organic matter in the sediments produces gaseous emissions to the water column. The exchange between bubbles ascending and the water column was measured. The model was calibrated with data obtained from a pilot facultative pond built in Muña Reservoir in Bogotá. The pond was sampled during 4 months to compare data between its water hyacinth covered section and uncovered section. The results clearly show the relative importance of different BOD removal processes in facultative ponds and suggest modifications to further improve performance. The results from the model suggest that internal loadings to facultative ponds due to solubilization and return of organic matter from the sediments to the aerobic layer greatly influence the soluble BOD effluent concentration. Aerobic degradation activity in the facultative pond does not affect significantly the effluent concentration. Anaerobic degradation activity in the facultative pond can more easily achieve increases in the removal efficiencies of BOD.