Local administrations are increasingly demanding real-time continuous monitoring of pollution in the sanitation system to improve and optimize its operation, to comply with EU environmental policies and to reach European Green Deal targets. The present work shows a full-scale Wastewater Treatment Plant field-sampling campaign to estimate COD, BOD₅, TSS, P, TN and NO₃⁻N in both influent and effluent, in the absence of pre-treatment or chemicals addition to the samples, resulting in a reduction of the duration and cost of analysis. Different regression models were developed to estimate the pollution load of sewage systems from the spectral response of wastewater samples measured at 380–700 nm through multivariate linear regressions and machine learning genetic algorithms. The tests carried out concluded that the models calculated by means of genetic algorithms can estimate the levels of five of the pollutants under study (COD, BOD5, TSS, TN and NO₃⁻N), including both raw and treated wastewater, with an error rate below 4%. In the case of the multilinear regression models, these are limited to raw water and the estimate is limited to COD and TSS, with less than a 0.5% error rate.

The study analyzes the flow over bottom racks made of longitudinal T-shaped bars. A clear water flow is considered in a laboratory flume. Free surface profiles, wetted rack lengths, and discharge coefficients are measured, changing parameters such as longitudinal slope, void ratio, and approaching flow. The present work complements existing experimental studies, considering the influence of the approaching flow conditions. The velocity field measured with Particle Image Velocimetry (PIV) technique and the pressure field with Pitot tubes are quantified. Numerical simulations (CFD) are used to complement laboratory data. The energy head along the rack is calculated and compared with the hypothesis of horizontal energy level with minimum energy at the beginning of the rack. A discharge coefficient adjustment that considers the slope, the void ratio, and the position along the rack is proposed and presented with the results of other works. Theoretical proposals to calculate the pressure field along the flow are compared with measurements in the laboratory. The relation between the static pressure head in the space of bars and the discharge coefficient is used as an alternative method to define the discharge.

Rainfall runoff collection in ephemeral streams is an objective in semi-arid zones. Rack intake systems are proposed to collect these flash floods with intensive sediment transport. The design parameters address the problem of clogging the spacing between bars. Experiments for two different void ratio racks are shown. Flows, longitudinal slopes in the rack, and water with three gravel-sized sediments were tested. Results such as effective void ratio due to the gravel deposition over the rack, the evolution of the flow rejected during each test, and the quantification of materials collected and deposited, are presented. The optimal longitudinal rack slope seems to be close to 30%. The effective void ratio is related to several hydraulic parameters calculated at the beginning of the rack. Some adjustments were proposed to predict the effective void ratio.

Spectrophotometry has proven to be an effective non-invasive technique for the characterization of the pollution load of sewer systems, enabling compliance with new environmental protection regulations. This type of equipment has costs and an energy consumption which make it difficult to place it inside a sewer network for real-time and massive monitoring. These shortcomings are mainly due to the use of incandescent lamps to generate the working spectrum as they often require the use of optical elements, such as diffraction gratings, to work. The search for viable alternatives to incandescent lamps is key to the development of portable equipment that is cheaper and with a lower consumption that can be used in different points of the sewer network. This research work achieved the following results in terms of the measured samples: First, the development a calibration procedure that enables the use of RGB-LED technology as a viable alternative to incandescent lamps, within the range of 510 to 645 nm, with high accuracy. Secondly, demonstration of a simple method to model the transmittance value of a specific wavelength without the need for optical elements, achieving a cost-effective equipment. Thirdly, it provides a simple method to obtain the transmittance based on the combination of RGB colors. Finally its viability is demonstrated for the spectral analysis of wastewater.

Bottom rack intake systems are one of the most popular structures for diverting water in steep rivers. Intake systems may be used in ephemeral rivers beds to capture part of the runoff flow in the rainy season. Their behavior has mainly been studied in the laboratory. Nevertheless, it is not possible to analyze the whole problem of characterization with traditional methodologies due to the many effects that occur on the bars. Computational fluid dynamics simulations have been considered as a complement to improve the knowledge of the hydraulic phenomenon. However, the geometry of circular racks may be a challenge due to its complexity. After the validation procedure, the numerical models appear to be a good tool to design intake systems. No remarkable differences were obtained between the three two-equation turbulence models tested. The results show differences of less than 1% in flow profile over the rack. Fit curves have been proposed to estimate the flow profile over the rack with r² > 95%. Expressions to calculate the discharge coefficient and the collected water through the rack in the clear water case have been proposed and show a good agreement with the laboratory data.

Although surface velocities are key in the calibration of physically based urban drainage models, the shallow water depths developed during non-extreme precipitation and the potential risks during flood events limit the availability of this type of data in urban catchments. In this context, imaging velocimetry techniques are being investigated as suitable non-intrusive methods to estimate runoff velocities, when the possible influence of rain has yet to be analyzed. This study carried out a comparative assessment of different seeded and unseeded imaging velocimetry techniques based on large-scale particle image velocimetry (LSPIV) and bubble image velocimetry (BIV) through six realistic but laboratory-controlled experiments, in which the runoff generated by three different rain intensities was recorded. First, the use of naturally generated bubbles and water shadows and glares as tracers allows unseeded techniques to measure extremely shallow flows. However, these techniques are more affected by raindrop impacts, which even lead to erroneous velocities in the case of high rain intensities. At the same time, better results were obtained for high intensities and in complex flows with techniques that use artificial particles. Finally, the study highlights the potential of these imaging techniques for measuring surface velocities in real field applications as well as the importance of considering rain properties to interpret and assess the results obtained. The robustness of the techniques for real-life applications yet remains to be proven by means of further studies in non-controlled environments.