Water distribution networks (WDNs) encounter pressure-deficient scenarios due to various operational disruptions including fire demand, pipe leakage, and pipe closure or bursting, and demand variation, each of which adversely affects nodal delivery. The behavior of pressure-deficient WDNs has been predicted using diverse techniques, namely source code modification, artificial element addition, and emitter-based modeling. Although pressure-driven analysis (PDA) was integrated into Environmental protection Agency network (EPANET 2.0) through its upgrade to version 2.2, the upgrade was constrained by the uniform desired pressure assumption—i.e., a single value of desired pressure applied to all nodes. In real large-scale WDNs, however, the desired pressure typically differs from node to node. This paper introduces a non-iterative modified C-code approach, termed as MCode, capable of simulating uniform and non-uniform desired pressures at individual nodes using the EPANET 2.2 toolkit. The study investigates the impact of both uniform and non-uniform desired pressure scenarios under pressure-deficient conditions through pressure-driven analysis. A comparative assessment of MCode against EPANET 2.2 PDA is conducted on benchmark case study networks for steady operating and extended period simulation (EPS). In proposed approach MCode assigning pressure requirements based on the condition of each node may be able to avoid any excess pressure while providing a sufficient service pressure at critical nodes, potentially. This can help to lower the risk of leaks and pumping needs, and help the operation become more efficient.
Global water scarcity demands urgent adoption of water-conserving practices in irrigated rice production. This field study, conducted in 2019 in Babolsar, northern Iran, evaluated the potential of deficit irrigation strategies delivered through a drip tape system to conserve water and sustain productivity in the Binam rice variety. Irrigation management treatments were based on maintaining soil water potential thresholds of 10, 30, and 60 kPa, applied either over the entire root zone (regulated deficit) or alternately to half of the root system (partial root-zone drying), alongside full drip irrigation and conventional flood irrigation as controls. Flood irrigation produced the highest grain yield (6442 kg ha⁻¹) but required the most water (10886 m³ ha⁻¹). In contrast, alternate partial drying at the driest threshold (60 kPa) achieved the greatest irrigation water productivity (1.39 kg m⁻³), a 135.6
Egypt’s water scarcity is influenced by multiple interacting factors, including climate change, growing water demand, domestic water-management challenges, and the evolving dynamics of transboundary Nile water governance, including the operation of the Grand Ethiopian Renaissance Dam (GERD). These pressures, compounded by climate change and domestic water management inefficiencies, intensify drought risk and threaten food security, rural livelihoods, and the Nile Delta ecosystem. Therefore, this study provides a comprehensive assessment of Egypt’s drought vulnerability by integrating climate projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6), TerraClimate data, and machine learning based drought modeling. Future climate projections indicate a temperature increase of approximately 1.8–2.2 °C under SSP2-4.5 and 3.5–4.2 °C under SSP5-8.5 by 2100, accompanied by a projected 5–15
The high demand for potable water and the unavailability of functional treatment facilities at Jabi Lake, with its toxic heavy metal and nutrient-contaminated water, necessitated the development of sustainable, environmentally friendly remediation technology to improve its quality. A corn-husk-biochar-modified Coix lacryma-jobi planted batch-flow-constructed wetland was developed to treat Jabi Lake water samples to reduce the heavy metals (Zn, Pb, Fe), nutrients (N, P, K) and other physico-chemical parameter concentrations. The Jabi Lake water characterization was done using standard procedures, with determination of concentrations of heavy metals using an Atomic Absorption Spectrophotometer (AAS). Three composite samples were taken from each of the four substrate types, which were made of sharpsand only (SSS-only), Quarry dust only (QD-only), biochar with sharpsand (A-SS) and biochar with Quarry dust (A-QD) under HRT-3 and 5. Sampling was replicated thrice, making a total of 72 samples. Water samples were tested before and after treatment in the constructed wetlands (CWs) for the same parameters previously tested. Corn husk was charred in a fabricated kiln and characterized before its application in the CWs. The biochar exhibited improved microporosity, which enhanced its sequestration capacity. The highest removal efficiencies (REs) obtained were COD (88.99
Water insecurity is a global challenge driven by multi-dimensional factors. Water insecurity threatens livelihoods and social wellbeing, and acts as a catalyst that shapes social relationships and community resilience in most localities. Nonetheless, there has been inadequate examination of the consequences or trickle-down effects of water insecurity in communities. Therefore, this study examined gendered burdens and violence at water collection points in six selected communities in the Nanumba Nanumba South District in the Northern Region of Ghana. The study adopted a cross-sectional study and employed a convergent mixed method approach. The study was conceptualized through the lens of Frustration-Aggression and Resource Scarcity Theories. Systematic and purposive sampling techniques were employed in selecting the study participants involving a survey of 312 household heads or their representatives and 25 key informants in the study communities. Additionally, six focus group discussions involving a total of 36 participants were conducted in the study communities. The qualitative themes that emerged included water scarcity, competition for water at water collection points and related violence in communities, gendered experiences in water collection and psychological impact on individuals engaged in water collection. Others include social cohesion and community dynamics, institutional management and communal water governance. The results of the study reveal that water insecurity exists as a social crisis, posing a serious threat to community health and weakening social capital in the communities. The study further reveals that 67.6
Wastewater treatment remains a major global challenge despite the continuous development of advanced treatment technologies. Constructed wetlands (CWs) have emerged as reliable, cost-effective, and environmentally sustainable systems that mimic natural wetland processes for wastewater purification. The treatment performance of CWs largely depends on the characteristics and efficiency of the filter media used as substrates for pollutant removal. In recent years, bio-based filter media have gained increasing attention as sustainable alternatives to conventional materials such as gravel and sand. These eco-friendly materials, including biochar, cork, agricultural residues, wood-based products, and other lignocellulosic by-products, exhibit high porosity, large specific surface area, and strong adsorption capacity while providing favorable conditions for microbial colonization and biofilm development. Consequently, they offer significant potential for enhancing pollutant removal in CW systems. This review provides a comprehensive overview of bio-based filter media applied in constructed wetlands for wastewater treatment. The physicochemical properties of these materials, their pollutant removal mechanisms, and their environmental benefits are critically discussed, together with their potential limitations. Recent studies are reviewed to assess their effectiveness in removing organic matter, nutrients, heavy metals, pathogens, and emerging contaminants. Furthermore, the review identifies current knowledge gaps and highlights future research needs related to long-term performance, large-scale implementation, material durability, and integration within circular economy frameworks.
Water scarcity is one of the most critical challenges facing many regions around the world, particularly in arid and semi-arid areas where access to clean water is limited and demand continues to rise. Due to the growing trend in population, industrialization, and climate change, sustainable and low-cost water purification strategies are of urgent need. The use of solar distillation has been identified to be a viable option because it makes use of renewable energy, is easy to operate, and can be decentralized. Traditional solar stills are, however less productive and with low thermal efficiency and this has necessitated technological improvement. This paper is a performance analysis of a Corrugated Modified Solar Still (CMSS) designed by incorporating three main improvements, which include rotating corrugated cylinders, cotton wick material, and the use of photovoltaic panels to power electrical heaters. The experiment was carried out through three days during May 2024 with different rotational speeds (0.2, 0.4, and 0.6 rpm) in order to identify the most efficient setup that would lead to the highest freshwater production. The modified design also incorporates a glass cover inclined at 33°, selected in accordance with the geographical latitude of Baghdad to enhance solar incidence and condensate flow efficiency. The results showed that the CMSS significantly outperformed the Conventional Solar Still (CSS) across all tested conditions. The optimal performance was achieved at a cylinder speed of 0.4 rpm, resulting in a cumulative distillate yield of 7465 mL/m²/day, compared to 1822.8 mL/m²/day for the CSS—representing a productivity increase of approximately 320
In tropical and semi-arid regions such as India, the escalating competition between agricultural freshwater demand and utility-scale solar energy expansion has created an acute food, energy, and water nexus conflict. To resolve this tension, this review synthesizes recent advancements across agrivoltaic structural design, microclimate modification, crop physiological water responses, and precision water management technologies. A quantitative synthesis of recent field trials indicates that, depending on crop and system configuration, agrivoltaic shading can reduce crop evapotranspiration and irrigation requirements by 19 to 47
Rivers in tropical semiarid basins are typically intermittent, experiencing prolonged periods of zero or very low discharge. This study evaluated the applicability of empirical concentration-flow (C-Q) relationships for assessing water quality in the Middle Jaguaribe river, the main tributary of the Castanhão reservoir, the largest water-supply reservoir in the Brazilian semiarid region. C-Q equations incorporating two terms representing point sources (PS) and non-point sources (NPS) were fitted to 8–12 measurements of electrical conductivity, turbidity, biochemical oxygen demand (BOD), thermotolerant coliforms (TTC), total phosphorus (TP), total inorganic nitrogen (TIN), and chlorophyll-a (Chla), all showing satisfactory predictive performance (R² = 0.37–0.94). While conductivity and TTC decreased and increased monotonically with river flow, respectively, the remaining parameters exhibited a characteristic two-regime behavior. At low flows, concentrations decreased with increasing discharge, reflecting dilution under PS dominance. Beyond a threshold flow rate, concentrations increased with discharge, indicating wash-off and enhanced transport from NPS. The estimated threshold flow rates, at which PS and NPS contributions became equal, were of the same order of magnitude as the watershed’s average sewage discharge, providing physical support for the proposed framework. Overall, NPS dominated pollutant transport during 89–100
Human activities and industrialisation have significantly deteriorated water quality, primarily due to the industrial and domestic wastewater effluents into natural water bodies. For prediction and monitoring its contents, previous studies rely mostly on standalone machine learning (ML) models, hybrid models with manually tuned hyperparameters. To monitor and provide a faster cost-effective monitoring system than standalone (ML) algorithms and manually tuned hyperparameters, this study has integrated extreme standalone ML techniques, including Extreme Gradient Boosting (XGB), Gene Expression Programming (GEP), and Support Vector Regression (SVR) with an advanced auto-tuning Particle Swarm Optimisation (PSO). Two critical wastewater parameters: Biological Oxygen Demand (BOD) and Total Suspended Solids (TSS) have been chosen among other constituents such as pH, COD, SSV, EC and Sediments. Further, a dataset comprising 527 samples, compiled from published studies, was divided into training (80
Access to safe drinking water remains a global challenge due to increasing contamination pressures from industrial, agricultural, and natural sources. Accurate classification of potable versus non-potable water is critical to ensuring sustainable water management. Traditional water quality monitoring methods, while precise, are limited by their cost, labor intensity, and inability to scale for real-time assessments. Machine learning approaches, particularly ensemble methods such as Random Forest (RF), have emerged as effective alternatives for water potability classification. This study proposes a hybrid Random Forest model enhanced with the Coati Optimization Algorithm (RF-COA) to optimize RF hyperparameters and improve classification performance. Using a publicly available dataset, RF-COA was compared against RF-RS, RF-BO, RF-CV, and RF-GS across multiple metrics, including classification accuracy (CA), G-mean, and Matthews correlation coefficient (MCC). The outcomes suggest that RF-COA consistently surpasses opposing techniques, maintaining a CA grade over 94
Reliable soil water balance models are needed for sugarcane water management under rainfed and non-standard field conditions. This study optimized crop coefficients and assessed the Thornthwaite and Mather Crop (ThM) and FAO-56 dual-Kc models for estimating daily and 10-day soil water content (θ) and actual evapotranspiration (ETa) in rainfed sugarcane in Alagoas State, Brazil. Field θ was measured with a reflectometry probe, and ETa was determined using the Bowen ratio-energy balance method. The Metropolis-Hastings algorithm implemented in OpenModel was used to optimize the mid-season crop coefficient (Kc_mid) for ThM, and the mid-season basal crop coefficient (Kcb_mid) and soil water depletion fraction (p) for dual-Kc, using measured ETa or θ as the optimization reference. The ETa-based optimized Kc and Kcb values were 0.89–0.90, lower than the FAO-56 tabulated values and close to the experimental Kc (0.79 ± 0.11), whereas θ-based optimization resulted in a Kcb of 1.04, and a very low Kc (0.38), suggesting parameter compensation. Daily ETa estimates improved mainly under soil water recharge (P – ETc ≥ 0), whereas both models performed poorly under soil water extraction (P – ETc < 0), indicating limitations in representing water stress and short-term soil water redistribution. Soil water content was simulated more consistently than ETa, especially after optimization. Aggregation to 10-day intervals improved model robustness, with dual-Kc performing better for ETa and ThM providing the best soil water estimates. Thus, the optimized models are useful for medium-term water balance assessment and irrigation scheduling but should be used cautiously for daily ETa estimation under water-stress conditions.
Reliable information on crop water-use dynamics is essential for improving irrigation management in water-limited regions; however, conventional weighing lysimeters remain expensive and operationally demanding, limiting their widespread application in developing countries. This study presents the development and field evaluation of an indigenized Smart Field Lysimeter (SFL) designed for relative assessment of crop water-use dynamics. The system integrates load-cell-based weighing, multi-depth soil moisture and soil temperature sensing, solar-powered operation, and a microcontroller-based data acquisition unit. The SFL was evaluated during a 120-day maize (Zea mays L.) growing season in Rawalpindi, Pakistan, where daily crop evapotranspiration (ETc) and growth-stage crop coefficients (Kc) were estimated using a mass-balance approach and compared with FAO-56 recommendations. Seasonal maize ETc was approximately 380 mm, with the highest water use occurring during the mid-season growth stage (167.6 mm; mean 4.19 mm day⁻¹). Mean crop coefficients increased from 0.34 during the initial stage to 1.15 during mid-season before declining to 0.60 during crop maturity. The temporal behavior of ETc and Kc broadly followed FAO-56 trends while exhibiting site-specific differences associated with local climatic conditions, crop development, and the experimental configuration. Continuous soil moisture and soil temperature monitoring further demonstrated stable system response to irrigation, rainfall, and crop development throughout the experiment. Although the results represent observations from a single lysimeter and growing season, the developed SFL proved capable of monitoring relative crop water-use dynamics and provides a practical, low-cost platform for exploratory irrigation and crop water-use research in data-scarce environments. Future work should focus on multi-season validation, replicated field experiments, and independent comparison with reference lysimeters.
Heavy metal contamination in aquatic environments is a serious ecological and human health problem that requires reliable monitoring and assessment. This review offers an integrated perspective on the key methods employed in heavy metal pollution monitoring, including pollution assessment indices, laboratory-based analytical methods, bioindicators, and newly developed real-time detection platforms. Widely used contamination indices are summarized, and their applicability, advantages, and disadvantages are critically discussed in this review. The review also covers the analytical techniques used for the quantitative determination of metals such as Atomic Absorption Spectroscopy (AAS), Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES), Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Atomic Fluorescence Spectroscopy (AFS), and X-Ray Fluorescence (XRF). The use of aquatic plants, algae, invertebrates, and fish as bioindicators is also discussed. Recent advancements in electrochemical, optical, biosensor-based, smartphone-assisted, and portable detection systems have been emphasized for rapid and on-site monitoring. The studies reviewed have shown that no single test approach can provide a complete assessment of contamination and ecological risk. Hence, the integration of pollution indices, laboratory validation, biological indicators, and sensor technologies is recommended for an integrated monitoring framework. Standardization, calibration, field robustness, and regulatory validation are still significant factors for future implementation.
Water scarcity and overexploitation from deep drilling threaten the sustainability of oasis agriculture in southern Tunisia and limit the long-term productivity of these agro-systems. Current irrigation systems and farming practices represent a major constraint, reducing long-term productivity and compromising the sustainability of adopted management plans. Most farmers in traditional oases use the submersion traditional irrigation practices. However, some have recently adopted micro-irrigation technology, though the impact of this shift on water use, yield, and date quality has been only partially evaluated. In this context, this study focuses on assessing these issues and estimating the water productivity of date palms through a field survey coupled with experimental work. The assessment covered water supply, yield, and fruit quality of palm trees under both irrigation systems. The experiment was conducted over two consecutive years (2016–2017) on two commercial farms cultivating the main economic variety, Deglet Nour, at the Hezoua oasis. Farmers irrigated with water supplied by the local users associations (GDAs), using either the submersion irrigation system (SIS) with traditional farmer scheduling or the Bubbler Irrigation System (BIS), which had been implemented since four years, based on crop water requirements. Data from the field investigation indicate that the average amount of irrigation water delivered by the GDAs to farmers was 25,348 m3ha−1/year for the SIS and 10,286 m3ha−1/year for the BIS. In addition, the average yield under both systems was 7.75 t ha−1 for SIS and 9.66 t ha−1 for BIS. Therefore, on average, the biophysical water productivity (WP) of date palms was 0.30 kg m−3 under traditional submersion irrigation and about 0.94 kg m−3 for the bubbler system. The results obtained during the experimental years for the selected farmers, along with additional field observations during 2016–2017, reveal that: (i) after four years of BIS implementation, the root system appears to adapt its density to the irrigation system; (ii) the use of BIS with appropriate scheduling reduced water supply by 40
Water scarcity is increasingly shaped by the interaction of physical limits, economic constraints, water-quality deterioration, and governance failure. This review synthesizes recent evidence on global water scarcity by examining climatic, anthropogenic, environmental, socio-economic, and political drivers; comparing regional manifestations; and evaluating mitigation options across technological, institutional, and nature-based domains. The review clarifies that scarcity should not be assessed only through per-capita volumetric indicators, because crisis conditions emerge when low availability coincides with poor access, unreliable infrastructure, degraded quality, weak institutions, and limited adaptive capacity. Agriculture remains the dominant freshwater-consuming sector, and therefore water-footprint management, crop planning, irrigation efficiency, deficit irrigation, drought-resistant crops, and allocation rules are central to any credible scarcity-reduction strategy. The analysis also compares interventions such as wastewater reuse, desalination, rainwater harvesting, managed aquifer recharge, efficient irrigation, economic instruments, groundwater monitoring, transboundary cooperation, and nature-based solutions in terms of feasibility, trade-offs, costs, and implementation risks. The review concludes that sustainable water security requires a differentiated response: physical scarcity demands demand management, reuse, allocation reform, and non-conventional supplies, whereas economic scarcity requires infrastructure investment, transparent governance, institutional capacity, and inclusive public participation.
Escalating groundwater salinity threatens the sustainability of deep desert aquifers in Kébili, Southern Tunisia, where groundwater is the only dependable freshwater source. In this study, groundwater quality and salinity conditions were assessed using an integrated framework combining hydrochemical analysis, selected water quality indices, ensemble machine learning modeling, and GIS-based spatial analysis. Forty-five groundwater samples were analyzed for major ions and physicochemical parameters to evaluate suitability for domestic and agricultural use. Key water quality indices (including Water Quality Index (WQI), Sodium Adsorption Ratio (SAR), and Sodium Percentage (Na
This study demonstrates the treatment of real laboratory effluents using a continuous-flow electrocoagulation (EC) reactor with aluminum electrodes. Under optimized conditions (pH 5.0, conductivity 6.89 mS/cm, current density 10 mA/cm², flow rate 0.1 L/min, HRT 120 min), removal efficiencies reached 83
Urban water security is a complex and multidimensional challenge. It extends beyond water availability to include quality, reliability, continuous access, and the long-term sustainability of services. This study investigates the urban water scarcity crisis in Tehran over a 150-year period (1875–2025) using the adaptive cycle framework. A mixed-methods approach was employed, combining historical data analysis, expert elicitation, and application of the cycle to identify stages of development, protection, collapse, and renewal in Tehran’s water governance structure. Originally designed for social-ecological systems, the adaptive cycle framework helps reveal recurring patterns of vulnerability and resilience. These dynamics are shaped by rapid urban growth, institutional changes, climate variability, and resource depletion. Results show that focusing solely on infrastructure development, without flexible governance, has increased rigidity and reduced the capacity to address emerging challenges. At present, Tehran’s urban water network is in the Contemporary Reorganisation (α) phase of the cycle. This stage is marked by two critical traps: the “Vagabond Trap,” caused by fragmentation of system components, and the “Poverty Trap,” driven by severe depletion of natural capital and resource scarcity. These traps intensify structural rigidities and resource limitations, constraining coordinated recovery and long-term functionality. The study concludes that overcoming Tehran’s water security crisis requires comprehensive and diversified management strategies. Key priorities include improving connectivity, increasing resource availability, fostering institutional innovation, and promoting broad stakeholder collaboration. Such approaches enable continuous learning and flexibility, contributing to the resilience of urban water services. They also enhance resource management practices in arid and water-scarce regions. By revealing adaptive cycles and critical traps in Tehran’s water framework, this research offers insights for designing future-oriented policies to address demographic and climatic pressures.
Agricultural irrigation has become one of the main drivers of pressure on water resources in the Araguaia River Basin (ARB) over the past three decades. This basin spans the Cerrado and Amazon biomes and, despite extensive research on land-use change and ecological impacts, it remains notably understudied with respect to how irrigation growth relates to the depletion of water resources. This study analyzes the expansion of irrigated areas from 1993 to 2023 and projects future scenarios for 2040 to support water-resource governance and agricultural planning. Using statistically corrected vector data, time-series analysis, and projection models, the study identifies significant spatial and temporal growth in irrigation. Compared with MapBiomas data, after manual correction, the irrigated areas under center pivots showed a 14.89
