Taza City is among the Moroccan cities which is in full urban expansion, with a daily wastewater discharge volume estimated at 16534 m3/d in 2020, and expected to reach 20056 m3/d by 2030. These waters, collected in a combined sewerage network, are directly released into the natural environment without any treatment. Indeed, a large part of this water is discharged into Oued Defali, the main tributary of Oued Larbâa. In order to manage and better understand these discharges impact on the streams crossing this city, wastewater sampling campaigns were carried out for one year from May 2018 to April 2019 at domestic (S1) and industrial (S2) sites. The wastewater physicochemical characterization revealed that these discharges are highly loaded with organic matter in terms of chemical oxygen demand (S1 avg = 1231.44 mg/l and S2 avg = 933.03 mg/l), biochemical oxygen demand (S1 avg = 511.87 mg/l and S2 avg = 464.35 mg/l), and suspended matter (S1 avg = 744.11 mg/l and S2 avg = 578.13 mg/l). The use of principal component analysis (PCA) has allowed us to collect as much information as possible from the database of the physicochemical analyses performed for the studied parameters.

Abstract. The region of Meknes suffers from a significant delay in the water sector, including sewage treatment. The Urban waste water in the region originates from various activities; households, industry, agriculture and hospital. These waters are released in to nature without any treatment, which constitutes a serious risk for the environment. The objective of this research is to characterize the physicochemical and bacteriological pollution of the three sewage collectors of the Meknes region (Aïn Choubbik, Oued Ouislane and Aïn Taoujdate). Indeed, the pollution parameters; biological and chemical oxygen demand are abnormally high, which indicates clearly that waste waters is rich of reducing or oxidizing organic materials. Ammonium, nitrogen, phosphorus and heavy metals concentrations exceed the limit values. So these waters are classified as bad or very bad quality. On the one hand, the presence of a large bacterial load indicates fecal contamination. The total coliform, fecal coliform and fecal streptococci levels are high exceeding exceed the values specified the WHO guidelines and the Moroccan standards. This situation is likely to cause serious and irreparable damage to the environment groundwater. To counter this, make the necessary investment in sewage treatment and other remedial measures is key to preventing pollution and its spread.

Abstract. Energy use in drinking Water Supply System represents an important part of the global energy consumption across all sectors. This portion is expected to raise, due to the raising demand and the recourse to unconventional water resources. For the water utilities, most of their operating costs are related to energy consumptions, especially the consumption of pumping systems. The main objective of this study is to produce a model which reflects the real behaviour of a pumping system to help in taking decisions on which pump to use First and which one to replace in case of a limited renovation. In order to do so, Multiple Linear regression was adopted to model the ratio kWh/m3 produced depending on the input parameters. The final model describes in a good manner the phenomenon (R2 = 0.91), so it can be a good estimator as the calculated ratio is close to the experimental one. The Novelty of this approach is to have a model which takes into account the real behaviour of the system whereas most of the studies focus on the pump scheduling problem.

Energy use in water supply systems represents a consequent part of global energy consumption across all sectors. This consumption is expected to rise, due to the increasing demand and the recourse to unconventional water resources. Regarding water utilities, most of their operating costs are related to energy consumption, especially pumping systems consumption. In this context, the main objective of this study was to model accurately by using data statistical analysis the energy consumption of pumping systems in order to optimize the whole water supply system, thus improving its efficiency, especially in the case of a limited renovation. For this purpose, Multiple Linear Regression was fitted to model the produced kWh/m 3 ratio costs according to the following Key-parameters associated to drinking pumping stations: i) active and reactive energies; ii) the daily produced water volume; iii) the power factor (Cosφ); iiii) and the operating time of each pump. The final model describes accurately the consumption per cubic meter produced with R-square statistic reaching 0.91 and value standard error is close to 5% were found. Therefore, this model could be considered a good estimator for the calculated ratio, which was close to the experimental one. In addition, this approach considers the system in the Real-Time-Data behavior, while most of the comparable studies focus on the pump scheduling problem estimator for the calculated ratio which was close to the experimental one.