Water Conservation and Management (WCM)

This study presents a comprehensive analysis of air pollutant emissions from Jordan’s Al-Baqa’a and As Samra wastewater treatment plants (2018-2023), revealing critical insights into the water-air quality nexus in arid urban environments. Through integrated geospatial modeling and dispersion analysis, we demonstrate that biological treatment processes generate hazardous hydrogen sulfide (H₂S) concentrations reaching 177 ppb (17.7 times Jordan’s standard), while synergistic interactions with nearby petroleum and pharmaceutical industries contribute 19-63% of ambient sulfur dioxide (SO₂) and nitrogen oxide (NO₂) loads. Recent findings identify methane (CH₄) as a previously underestimated emission component, with biogas composition averaging 62±8% CH₄ by volume and contributing 14% of facility carbon footprints (1,230 tCO₂e/yr). The research identifies distinct seasonal patterns, with summer temperatures accelerating microbial conversion rates (Q₁₀=2.3) to produce NO₂ peaks of 181 ppb – 2.3 times the national limit. New VOC measurements reveal benzene levels (2.1±0.8 ppb) exceeding WHO cancer risk thresholds in 17% of samples near industrial zones. Our methodology combines high-resolution terrain modeling (30m SRTM data) with validated atmospheric simulations (COD=0.27, |FB|=0.18) to quantify exposure disparities, showing communities near WWTPs endure particulate matter concentrations 4.7 times higher than background areas. The findings inform three actionable mitigation pathways: process optimization through extended sludge retention (15.3±1.2 days) reduces H₂S by 41%, chemical scrubbers achieve 89% SO₂ removal, and IoT-enabled smart systems to cut NO₂ peaks by 33%. This work establishes wastewater infrastructure as a critical frontier for urban air quality management, providing both immediate solutions for Jordan’s regulatory compliance and a transferable framework for addressing the climate-pollution nexus in water-stressed regions worldwide.

Groundwater is vital for socio-economic development worldwide, as it sustains communities and supports various industries. Indonesia, especially the island of Java, has a unique geological setting, characterized by a volcanic aquifer associated with andesitic stratovolcanoes, which contributes to the availability of highquality groundwater. However, groundwater in volcanic terrains is often complex and unidentified due to heterogeneous subsurface conditions, particularly in regions experiencing water scarcity and environmental degradation. This study employed Electrical Resistivity Tomography (ERT) using the ADMT 300HT2 to characterize aquifers in seven villages of Probolinggo Regency, East Java. The research encompasses seven
villages: Maron Kidul, Wonorejo, Sumberan, Brumbungan Kidul, Jangur, Tegasan Kidul, and Alas Tengah. The results revealed resistivity values ranging from 0.3 to 60 Ωm, with low values (<5 Ωm) indicating clay-rich impermeable layers and higher values (>30 Ωm) corresponding to productive aquifers such as volcanic sandstone, sandy breccia, and silt sand. Aquifers were identified at depths of 20–50 m (unconfined) and >100 m (confined), with the highest potential observed in Wonorejo, Sumberan, and Tegasan Kidul villages. These findings provide crucial insights for local government authorities, offering hydrogeologically based recommendations for optimal drilling sites and facilitating the development of sustainable groundwater management strategies in Probolinggo Regency.

This study investigates how groundwater table (GWT) fluctuations control real-time slope deformation in an open-pit coal mine and quantifies their effect on slope safety factor (SF). The research purpose is to establish the statistical link between GWT rise and deformation velocity measured by Slope Stability Radar (SSR), estimate landslide time using the inverse-velocity method, and evaluate SF sensitivity to GWT using the Bishop Simplified Method to inform an adaptive Triggered Action Response Plan (TARP). Field monitoring with SSR was carried out over 5 days (30 Sep–4 Oct 2024) on the southern slope of Pit Banko (Tanjung Enim, South Sumatra), complemented by laboratory shear tests and stability simulations. We find a strong correlation between GWT rise (~70→90 m asl) and velocity acceleration (2.88→22.51 mm/h), culminating in a medium-scale failure. The best failure-time prediction (VCP-60) differed by only 44 minutes from the actual event. Each 5 m increase in GWT reduced SF by 18.7%, underscoring groundwater control as a critical mitigation lever. The SSR+GWT-based TARP reduced false alarms and sharpened response triggers, aligned with Indonesian regulations and international guidance. The novelty of this study is integration of real-time SSR deformation with groundwater-sensitive SF to drive threshold-based TARP decisions in a tropical open-pit context.

Water plays a key role in sustaining life, promoting social equity, and eradicating poverty, yet the management of transboundary water resources is often accompa-nied by geopolitical challenges. This article examines issues related to access and governance of water resources in Central Asia, where river basins hold significant ecological and economic importance. The scope of water-related problems in the region, their geopolitical dimensions, existing legal frameworks for transboundary water management, and the potential of cooperative strategies for sustainable wa-ter resource management are analyzed. Special attention is given to the institution-alization of water conflicts, which have acquired an environmental dimension, as well as the development of approaches to assessing resilience and reducing water stress. The findings and recommendations presented in the article aim to contrib-ute to the development of more effective solutions at local and regional levels.

A steady-state groundwater flow model was proposed to examine how rising water demand in Erbil City affects the groundwater level in Northern Iraq. In GMS 10.8.6, the model was developed and it was calibrated to 2007 data of groundwater levels for 13 wells by going through a trial-and-error optimization process. GMS used the Newton Solver package (NWT) to strengthen the accuracy and consistency of its groundwater flow calculations. Model quality was evaluated using statistical indicators (ME, MAE, RMSE, and NSE). The calibration performance reached 0.962 in 2007, while for the years 2010, 2013, 2016, 2019, 2022, and 2024 the values ranged between 0.809 and 0.966 during validation. The forecasts for the future were done for the years 2027, 2029, 2031, 2033 and 2035 by assuming different rates of groundwater abstraction (20% for 2027 and going up to 100% in 2035) and groundwater recharge used the monthly average rainfall values from 1991 to 2022. Groundwater dropped citywide as demand for water increased. Groundwater head trends, estimated using Mann-Kendall and Sen’s slope, found every observation well displayed extreme downward trends (p = 0.027), suggesting a steady decrease in all the areas. The values of R² between what the model predicts and what happens in reality were from 0.827 to 0.972, showing that the model works very well. In ArcMap 10.8, the spatial interpolation shown consistent descent of groundwater levels across several urban areas. It is necessary to create planning for water resources now and in the future and to target interventions where big drops are noticed. With the model, we can estimate how groundwater responds to future urban water demand

Emerging pollutants (ECs), such as drugs, cosmetics, pesticides, and endocrine disruptors, are highly resistant to wastewater treatment and tend to be toxic and persistent. The conventional treatment processes are not efficient in removing micro-pollutants. Hybrid membrane technologies, which combine membrane filtration with advanced oxidation, adsorption, or biotechnology, offer improved removal efficiency while minimizing membrane fouling. This article critically assesses the majority of the most critical hybrid configurations, such as membrane bioreactors (MBRs), membrane-adsorption systems, and membrane-photocatalysis, emphasizing their mechanisms, operating efficiency, and removal capacity of effluent contaminants. The article also addresses integration schemes and highlights future challenges related to cost and sustainability

Heavy metals and organic dyes present in industrial wastewater pose significant risks to human health and the environment. Among available treatment methods, the advanced oxidation process (AOP) has gained attention for its ability to achieve complete degradation and removal of such contaminants. This study aims to synthesize a TiO2-reduced graphene oxide (rGO) composite and evaluate the role of each component in the combined adsorption-desorption and photocatalytic degradation mechanisms. The rGO was derived from agricultural waste—sugarcane bagasse and coconut shell—and combined with TiO2 via a hydrothermal method. The resulting composites, C-SB (from sugarcane bagasse) and C-CS (from coconut shell), demonstrated effective removal of Cu(II) and methylene blue (MB). C-SB achieved removal efficiencies of 87% for Cu(II) and 46% for MB, slightly outperforming C-CS with 76% and 44%, respectively. TiO2 exhibited a dominant photocatalytic effect in MB degradation, while rGO primarily facilitated Cu(II) removal through adsorption. The adsorption-desorption phase was found to significantly influence the photocatalytic efficiency. Kinetic analysis indicated that a pseudo-first-order model best described the MB adsorption-desorption process (R2 = 1), while a first-order kinetic model effectively represented the photocatalytic degradation, with R2 values of 98.68% for C-SB and 95.67% for C-CS. These findings highlight the potential of TiO2-rGO composites, especially those derived from sugarcane bagasse, in treating complex wastewater through a synergistic mechanism of adsorption and photocatalysis.

Access to safe drinking water remains a pressing global issue, with over 2.2 billion people still lacking safely managed water services. In Indonesia, rural communities often face disparities in access, relying on decentralized systems with limited sustainability. This study investigates financing mechanisms for community-based rural water utilities (RWS) in Piyungan Subdistrict, Bantul Regency, to identify suitable models that support long-term service sustainability. By employing Analytical Hierarchy Process (AHP) method, this research analyzes social, economic, and environmental criteria and sub-criteria influencing financing preferences from the RWS. Primary data were collected through structured interviews and questionnaires with eight RWS entities meeting specific performance and operational criteria. The results show that social factors, particularly community-based management and participation, are the most influential in sustaining RWS. Among four financing alternatives, community financing emerged as the most preferred (62%), followed by private financing and grants, with debt financing receiving the lowest priority. These findings highlight the critical role of local engagement, institutional capacity, and adaptive financial strategies in ensuring service continuity. The study proposes a phased, blended financing approach, tailored to each stage of RWS development, emphasizing that long-term sustainability must be supported by institutional reforms, improved financial management, and environmental risk governance.

In regions of Uzbekistan where water resources for irrigation are limited, drip irrigation optimization is of great importance. This study evaluated the effectiveness of the AdaptiveDrip-Uz system. This system includes HYDRUS 2D/3D modeling, artificial intelligence (AI) module, real-time IoT sensors, and GIS-based monitoring components. The model, built on 30 days of field data, automatically controls the irrigation regime based on humidity, temperature, evapotranspiration, and salinity. Of the various AI models, ANN (Artificial Neural Networks) showed the highest accuracy (R2 = 0.951), resulting in a 27% reduction in water consumption and a 24% increase in yield. Moisture and salinity contours, sensor analysis, and a 3D visual interface created through HYDRUS confirmed the high efficiency and flexibility of the system. A SWOT analysis of the system was also conducted, identifying its strengths and weaknesses, and evaluating it as a practical and sustainable innovative solution in the agroecosystems of Uzbekistan. The AdaptiveDrip-Uz model serves as a practical example of a real-time digital agriculture approach adapted to climate change.

This study investigates sustainable water resource management strategies for Bueng Si Fai, an ecologically and socio-economically important freshwater wetland in Thailand. It aims to identify and prioritize strategic alternatives by assessing the relative importance of environmental, social, economic, and technological criteria using the Analytic Hierarchy Process (AHP). Data were collected via questionnaires and interviews with 20 experts in water management and sustainable development. Results show environmental factors as most influential (32%), particularly forest and wetland abundance (27%), followed by social (29%) and economic (24%) factors, with community development and local economic stability as key sub-criteria. Technological factors had the lowest weight (15%), though increasing water availability was prioritized. Biodiversity conservation emerged as the top strategic goal (41%), underscoring the need to embed ecological priorities within development plans. The findings validate AHP as an effective tool for complex decision-making and emphasize a holistic, participatory approach to sustainable water management. This framework offers a transferable model for similar wetland ecosystems