Given the critical importance of addressing effluent quality concerns, the present study was dedicated to developing a dynamic simulation model based on the Activated Sludge Model 1 (ASM1) of a wastewater treatment plant located in Maghnia City, Algeria. The model calibration process involved collecting and analyzing 56 samples from the plant over a period of 18 months (from July 2021 to January 2023). Thirteen physicochemical parameters were analyzed to identify the variations in their water quality over time. Stoichiometric and kinetic parameters were adjusted during the plant calibration process. These modifications resulted in a reasonable alignment with the investigated variables, enabling the accurate prediction of the wastewater treatment plants (WWTPs)’ steady-state behavior regarding the removal measurements of chemical oxygen demand (COD), total suspended solids (TSS), and ammonium (NH4-N). The model was validated using 14-day measurements spanning a 4-month duration, and the results indicated good agreement between the observed and simulated effluent variable of chemical oxygen demand (COD) with a root mean square error (RMSE) of 23%. These findings highlight the utility of the ASM1 Model in comprehending and managing the intricate dynamics of the activated sludge process in wastewater treatment plants.

Water infrastructure management relies on information, communication strategies, and affordable technologies. This paper used demand analysis and modeling to guide strategic decision-making in sustainable water management for the urban cluster in Tlemcen, Algeria. To achieve this, the water supply and demand of the study area were assessed over the past three decades. The Water Evaluation and Planning (WEAP) system was employed considering different future scenarios to help decision-makers consider the best choices for sustainable urban water resources management. The results showed that the average water production and distribution efficiency was only 46% due to the high network loss. Therefore, urgent action should be considered to increase the efficiency of the distribution network. Moreover, the outcome showed severe unmet demand in 2050, which can be managed by improving the water networks, increasing conventional water production, and reducing personal water consumption. In cooperation with key stakeholders, new scenarios can be analyzed to develop efficient water management policies and to implement sustainable water allocation approaches.

Algeria faces severe water stress, marked by a decrease in water availability per inhabitant from 1,500 m ³ /year in 1962 to 430 m ³ in 2020, with a projection of 300 m ³ by 2050. In this context, optimizing wastewater treatment plants (WWTPs) becomes essential to reduce the water deficit. This study evaluates the performance of the urban wastewater treatment plant of Maghnia (Northwestern Algeria) by carrying out a statistical analysis of physicochemical parameters and comparing the Weighted Arithmetic Water Quality Index (WAWQI) and Water Pollution Index (WPI) based on data collected between January 7, 2020, and March 22, 2021. Reliable detection of outliers was achieved through the combined application of Grubbs and Tukey tests, while data normality was verified by Shapiro–Wilk, Anderson–Darling, and the P-P plot, thus strengthening analytical robustness and minimizing bias. The results show stability of physical parameters (temperature and pH) and moderate variability of chemical parameters, including chemical oxygen demand (COD), total suspended solids (TSS), and biochemical oxygen demand (BOD₅), at the plant inlet. However, notable exceedances of standards at the outlet were observed, notably for ammonium (7.92 mg/l, standard limit: 5 mg/l) and phosphates (10.01 mg/l, standard limit: 2 mg/l), indicating deficiencies in biological treatment despite high organic matter removal efficiency. Bland–Altman analysis confirms the complementarity of the WAWQI and WPI indices, highlighting low quality of treated water and chronic system overload. These results underscore the need for targeted process optimization, particularly for nutrient removal, to ensure safe reuse of treated wastewater.

The Ghrib Basin is currently encountering water-related challenges due to population growth and growing competition among water users. Therefore, assessing the current water situation is essential for the anticipation of future needs in the region. This paper assesses water demand and allocation strategies in the Ghrib Basin, Algeria, using the Water Evaluation and Planning (WEAP) system. The simulation is based on five scenarios: “Increase in population and agricultural activity”, “Improving agricultural activity”, “Minimum domestic consumption”, “Enhancing Water Resources”, and “Best practice”, (which is a combination of two scenarios, i.e., “Improving agricultural activity” and ”Minimum domestic consumption”). The simulation outcomes indicate that the “Best practice” scenario represents the most advantageous and beneficial scenario by which the problem of the unmet demand can be solved. The resulting simulations indicated the need for the employment of water-efficient irrigation systems as well as the encouragement of sustainable water use, such as drip irrigation, which necessitates coordinated efforts and particular infrastructural investments. The derived outcomes are highly convincing and have the potential to serve as a decision support system for the effective governance of water resources in the Ghrib Basin. The methodology utilized in this study has the potential to be implemented in any basin across the globe.

This study investigated groundwater suitability for irrigation in the Hennaya Irrigated region of Northwest Algeria. The research pursued two primary objectives: first, to establish the hydrochemical origin of the groundwater through comprehensive analyses including hydrochemical parameters, diagrams, and hierarchical clustering; and second, to assess its suitability for irrigation based on key criteria such as the Water Quality Index (WQI), Wilcox, and US Salinity diagrams. The analysis revealed a high level of groundwater suitability for irrigation, as indicated by various indices: Sodium Adsorption Ratio (SAR) values ranged from 1.69 to 2.55 (Excellent), Sodium Percentage (Na%) ranged from 24.22% to 36.98% (Good), and the Residual Sodium Carbonate (RSC) was negative, falling between −8.91 to −1.70 meq/L (Safe). Kelly’s Ratio (KR) ranged from 0.32 to 0.59 (Good), and the Permeability Index (PI) was between 62% and 99% (Moderate). Supported by the Analytic Hierarchy Process (AHP) and spatial analysis, the Water Quality Index (WQI) values ranged from 69.25 to 88.71, categorizing the groundwater in the study area as ‘Good’ quality. While suitable for irrigation, the groundwater showed slight salinity (EC 1247–2010 μS/cm) and alkalinity (pH 7.09–8.02), with elevated total dissolved solids (TDSs) ranging from 990 to 1930 mg/L, approaching the permissible limits for optimal agricultural use. The dominant ion concentrations (Ca²⁺ > Na⁺ > Mg²⁺ > K⁺; HCO₃⁻ > Cl⁻ > SO₄²⁻ > NO₃⁻) indicate a mixed hydrochemical facies influenced by both water–rock interactions and evaporative processes. Although these findings are promising, they highlight the necessity for preventive measures. Ongoing proactive management and continuous monitoring are essential to ensure the long-term sustainability and protection of groundwater resources in the region.

Three-step graphic showing the ASM1 calibration workflow for the Ain Elhoutz wastewater plant: routine effluent COD data are fractionated and four parameters are optimised at 18 °C, then the same parameters are validated at 22 °C without re-tuning. Mechanistic simulation of municipal activated sludge plants relies predominantly on Activated Sludge Model No. 1 (ASM1), yet routine application is hindered by over-parameterisation: calibrating the full kinetic set to dynamic plant data invites equifinality and loss of predictive power. This study develops a sensitivity-Driven ASM1 calibration workflow for a low-load plant in north-western Algeria, extending our earlier steady-state and dynamic simulation work in the region. ASM1 was implemented in GPS-X, and influent chemical oxygen demand (COD) was fractionated using the CEMAGREF protocol supplemented by a post-calibration mass-balance adjustment. Four parameters (XBH, μmax, H, YH, and KS), the subset repeatedly identified as dominant for effluent COD variance and practically identifiable in recent sensitivity and collinearity studies, were optimised against a targeted dynamic calibration window at 18 °C using the Nelder–Mead simplex algorithm and then tested on an independent seasonal dataset at 22 °C. Calibration achieved strong agreement (ℛ2 = 0.79), validation confirmed acceptable predictive performance (ℛ2 = 0.68) with no systematic bias, while the uncalibrated nitrogen variables showed a consistent over-prediction, quantified and attributed in Section 3. Requiring only routine COD data, the workflow provides a transferable, operator-grade template for dynamic ASM1 calibration at municipal plants with comparable monitoring programmes.