Search Results (713)

Growing pressures on water resources, exacerbated by climate change, resource depletion, and population growth, underline the need for sustainable and energy-efficient wastewater management. Wastewater treatment plants (WWTPs) are among the most energy-intensive elements of the Integrated Water Service, and their environmental performance depends on infrastructure design, resource availability, and treatment configuration. Improving resource efficiency while reducing energy demand and environmental impacts is therefore a priority for water utilities seeking innovative decision-support tools. Within the national project “WATERGY—Energy Efficiency of the Integrated Water Service”, this study proposes a life-cycle-based framework to assess the sustainability of technological interventions in WWTPs. A comparative gate-to-grave Life Cycle Assessment (LCA) was applied to the municipal WWTP of Potenza (Southern Italy). Three sludge End-of-Life Scenarios were assessed: the current landfill-based configuration, an enhanced oxygenation–nitrification setup, and anaerobic digestion with biogas-based cogeneration. Compared to the current scenario, anaerobic digestion with cogeneration reduces Global Warming Potential by 17% and decreases freshwater ecotoxicity by approximately 30%. Compost production shows the highest reduction in ecotoxicity (−51%) but increases fossil resource depletion and acidification due to higher energy demand. Overall, energy recovery pathways, particularly anaerobic digestion with cogeneration, provide the most balanced environmental benefits, supporting more sustainable WWTP operation within the Integrated Water Service. Full article

Quantitative evaluations in 3D images acquired via Cone-Beam Computed Tomography (CBCT) are limited by the scatter abundance and cone-beam artifacts. This work investigates benefits in using an innovative scanning geometry in CBCT (eCT), which replaces each projection of the conventional scanning protocol with a series of collimated projections (Np) acquired over an oscillating trajectory, realized either with an oscillating source or a multi-spot array. In silico tests employed a cylindrical water phantom embodying inserts of four biological materials. 1 mm-thick bone slabs were sandwiched between 9 mm water slabs to evaluate the image conspicuity. eCT improved the Hounsfield Unit (HU) accuracy, with a direct relation with Np. eCT with Np = 10 reduced the bias of the estimated HU more than two times when compared to CBCT. Increasing the Np presented a large impact on the image conspicuity for portions of the FOV distant from the central axial plane, with the signal-to-noise ratio between water and bone slabs increasing by a factor of 18 for Np = 10 compared to CBCT. The proposed eCT configuration is expected to be adopted in applications without strict demand for scanning time and projection number, such as dentomaxillofacial and intrasurgical imaging, imaging of the extremities, and image-guided radiotherapy. Full article

District heating systems are central to Europe’s decarbonisation strategy and its 2050 climate-neutrality objective. However, district heating is deeply embedded in the socio-economic system and the built environment. This makes compliance with policy targets at the local level particularly challenging. The issues are attributable to two factors. Firstly, the process is characterised by a high degree of complexity and multidimensionality. Secondly, there is a scarcity of local resources (e.g., land, surface waters, waste heat, etc.). In Bucharest, Romania, the largest district heating system in the European Union, the process of decarbonisation represents a particularly complex challenge. The system is characterised by large physical dimensions, high technical wear, heavy dependence on natural gas, significant heat losses and complex governance structures. This paper presents a strategic planning exercise for aligning the Bucharest system with the Energy Efficiency Directive 2023/1791. Drawing on system data, investment modelling, and local resource mapping from the LIFE22-CET-SET_HEAT project, the study evaluates scenarios for 2028 and 2035 that shift heat generation from natural gas to renewable, waste heat, and high-efficiency sources. The central objective is the identification of opportunities and issues. Options include large-scale heat pumps, waste-to-energy, geothermal and solar heat. Heat demand profiles and electricity price dynamics are used to evaluate economic feasibility and operational flexibility. The findings show that the decarbonisation heat supply in Bucharest is technically possible, but financial viability hinges on phased investments, interinstitutional coordination, regulatory reforms and access to EU funding. The study concludes with recommendations for staged implementation, coordinated governance and socio-economic measures to safeguard heat affordability and system reliability. Full article

The Tibetan Plateau (TP) has experienced pronounced climate change over recent decades, yet the coupled interactions and trade-offs between vegetation dynamics and water yield (WY) remain insufficiently quantified. In this study, we employed the Lund–Potsdam–Jena (LPJ) model to simulate the spatiotemporal evolution of net primary productivity (NPP) and WY across the TP from 1981 to 2060, and applied the Geodetector method to identify the dominant drivers of vegetation dynamics. The results showed that: (1) during 1981–2020, both NPP and WY generally increased across the TP but exhibited distinct spatial patterns, with NPP showing more widespread and pronounced increases than WY; (2) sensitivity experiments revealed that a 2 °C warming substantially increased NPP (+48.79%) but suppressed WY (−17.96%), whereas a 25% increase in precipitation resulted in only a modest rise in NPP (+5.72%) but a sharp increase in WY (+46.72%); (3) the driving factor analysis showed that precipitation, temperature, and WY were the primary controls on NPP, while interaction analysis revealed that their combined effects explained NPP variability more effectively than individual factors; (4) under the Shared Socioeconomic Pathways (SSPs), vegetation–water interactions were projected to shift, with continued greening intensifying water depletion in arid regions, while humid regions were more capable of meeting increased water demand. These findings enhance understanding of vegetation–water coupling across the TP and provide a scientific basis for evaluating future ecohydrological risks under climate change. Full article

Recent projections by the Intergovernmental Panel on Climate Change indicate that global warming will turn permanent and further intensify the severity and frequency of extreme weather events (heat waves, rain, and intense droughts), with coastal regions being the most vulnerable to extreme events. Therefore, the risk of natural disasters and the associated regional impacts on water, food, energy, social, and health security represents one of the world’s greatest challenges of this century. However, conventional methodologies for monitoring these regions during extreme events are usually not available to managers and decision-makers with the necessary urgency. The aim of this study was to present a framework concept for assessing extreme flood event impacts in coastal zones using a suite of field data combined with numerical (hydrological, meteorological, and hydrodynamic) and computational (flooding) models in a virtual environment that provides a replica of a natural environment—the Patos Lagoon Digital Twin. The study case was the extreme flood event that occurred in the southernmost region of Brazil in May 2024, considered the largest flooding event in 125 years of data. The hydrodynamic model calculated the water levels around Rio Grande City (MAE ± 0.18 m). These results fed the flooding model, which projected the water over the digital elevation model of the city and produced predictions of flooding conditions on every street (ranging from a few centimeters up to 1.5 m) days before the flooding happened. The results were further customized to attend specific demands from the security forces and municipal civil defense, who evaluated the best alternatives for evacuation strategies and infrastructure safety during the May 2024 extreme flood event. Flood Safety Maps were also generated for all the terminals in the Port of Rio Grande, indicating that the terminals were 0.05 to 2.5 m above the flood level. Overall, this study contributes to a better understanding of the strengths of digital twin models in simulating the impacts of extreme flood events in coastal areas and provides valuable insights into the potential impacts of future climate change in coastal regions, particularly in southern Brazil. This knowledge is crucial for developing targeted strategies to increase regional resilience and sustainability, ensuring that adaptation measures are effectively tailored to anticipated climate impacts. Full article

Demand for irrigation water varies substantially between upstream and downstream reaches of river basins due to spatial variability in rainfall, agro-climatic situations, and management practices. Upstream areas often experience over-irrigation and waterlogging, while downstream regions are challenged with water scarcity, timing mismatches, and allocation conflicts. This study proposes a novel SWAT–AquaCrop–optimization nexus framework to minimize both the frequency (DDF) and severity (DDS) of irrigation demand deficit under hydro-climatic uncertainty. To enhance numerical stability and a realistic representation of system stress, deficit frequency is formulated using a smooth, differentiable exceedance function instead of conventional binary thresholds. The framework integrates SWAT-based hydrological projections with AquaCrop simulations of crop yield and evapotranspiration-driven water demand, simultaneously evaluating three interlinked objectives: allocation-disparity deficit (equity), yield deficit (productivity), and irrigation-efficiency deficit (operational performance). Hydro-climatic uncertainty is represented through a quantile-based classification, with favorable (S₁), normal (S₂), and extreme (S₃) scenarios defined by the 33rd and 66th percentiles of the time-varying deficit ratio. The results indicate that stage-specific irrigation timing adjustments (advanced by 2–5 days) better align water applications with peak crop water requirements during flowering and grain-filling stages. This enhances downstream reliability, mitigates upstream over-irrigation, and substantially reduces both demand deficit frequency and severity. Full article

This study develops an integrated methodological framework coupling CMIP6 climate projections with a socio-economic-hydrological System Dynamics (SD) model to evaluate adaptation strategies for agricultural resilience. Applied to the Qazvin Plain aquifer in Iran, the model demonstrates high fidelity in capturing hydrological–human interactions, evidenced by a 97% correlation between simulated and observed groundwater levels. The system was developed using long-term meteorological drivers (1993–2024) and calibrated against observed socio-hydrological data for the period 2006–2024 and projected to 2062 under multiple CMIP6 scenarios, identifying SSP245 and SSP126 as the most accurate predictors for regional precipitation and temperature, respectively. Modeling outcomes indicate that aridity will intensify across all scenarios; specifically, under current water-use patterns, groundwater storage is projected to decline by 24.5%, 25.4%, and 27.6% by 2041 under SSP126, SSP245, and SSP585, respectively. However, the simulation reveals that integrating demand-side management with crop pattern optimization can stabilize the aquifer and boost agricultural value added by 7.4%. The findings further highlight that a 48% reduction in current groundwater withdrawals is essential to reach a sustainable threshold of 781 million m³. These quantitative insights suggest that while climatic pressures are increasing, human-driven management remains the decisive factor, provided that economic tools and smart monitoring are prioritized for long-term sustainability. Full article

Concrete arch dams represent a predominant dam type in water conservancy and hydropower projects in China. The control of concrete placement progress during construction directly impacts project quality and construction efficiency. Traditional manual monitoring methods, characterized by delayed response and strong subjectivity, struggle to meet the demands of modern intelligent construction management. This study introduces machine vision technology to monitor the concrete placement process and establishes an intelligent analysis system for construction scenes based on deep learning. By comparing the performance of U-Net and DeepLabV3+ semantic segmentation models in complex construction environments, the U-Net model, achieving an IoU of 89%, was selected to identify vibrated and non-vibrated concrete areas, thereby optimizing the concrete image segmentation algorithm. A comprehensive real-time analysis method for placement progress was developed, enabling automatic ternary classification and progress calculation for key construction stages, including concrete unloading, spreading, and vibration. In a continuous placement case study of Monolith No. 3 at a project site, the model’s segmentation results showed only an 8.2% error compared with manual annotations, confirming the method’s real-time capability and reliability. The research outcomes provide robust data support for intelligent construction management and hold significant practical value for enhancing the quality and efficiency of hydraulic engineering construction. Full article

Climate change and increasing groundwater demand underscore the urgency of sustainable water resource planning. Managed Aquifer Recharge (MAR) represents a promising strategy, yet its implementation depends on accurately identifying locations suited for specific MAR techniques. This study presents a GIS-based methodology developed under the DEEPWATER-CE project for identifying suitable locations for six MAR techniques in Central Europe. The methodology integrates environmental, hydrological, and land use criteria in a two-stage approach: an initial screening to delineate potentially suitable areas, followed by a detailed classification of those areas into high, moderate, and low suitability categories. The approach was tested in the Polish part of the Dunajec River catchment (4835 km²), revealing that river or lake bank filtration, infiltration ditches, and underground dams are the most viable MAR options, suitable for 12.6%, 13%, and 15.6% of the catchment area, respectively. A focused analysis within the Tarnów agglomeration, identified as highly vulnerable to climate change and with intensive groundwater use, demonstrated that 83–87% of the area is moderately suitable for infiltration ditches and riverbank filtration techniques. This decision-support tool can inform water managers and planners regarding the best locations for implementing MAR to enhance aquifer resilience, ensure water availability, and mitigate the impacts of extreme weather events. The methodology is transferable to other regions facing similar hydroclimatic challenges. Full article

The combined effects of climate change and socio-economic development have intensified the risk of water supply–demand imbalance in China. To project future trends, this study develops a multi-scenario coupled prediction framework integrating climate, socio-economic, and human activity drivers, combining data-driven and physically based modeling approaches to assess terrestrial water storage imbalance in nine major river basins under six representative SSP–RCP scenarios through the end of the 21st century. Using ISIMIP multi-model runoff outputs along with GDP and population projections, agricultural, industrial, and domestic water demands were estimated. A Water Conflict Index was proposed by integrating the Water Supply–Demand Stress Index and the Standardized Hydrological Runoff Index to identify high-risk basins. Results show that under high-emission scenarios, the WCI in the Yellow River, Hai River, and Northwest Rivers remains high, peaking during 2040–2069, while low-emission scenarios significantly alleviate stress in most basins. Water allocation inequity is mainly driven by insufficient supply in arid northern regions and limited redistribution capacity in resource-rich southern basins. Targeted strategies are recommended for different risk types, including inter-basin water transfer, optimization of water use structure and pricing policies, and the development of resilient management systems, providing scenario-based quantitative support for future water security and policy-making in China. Full article

Water diversion projects are a crucial measure for addressing eutrophication in shallow lakes worldwide. However, the impacts of different water diversion operation schemes on lake hydrodynamics and water quality can vary significantly, necessitating targeted, refined simulation assessments. This study focuses on Chaohu Lake, one of China’s most eutrophic lakes, and uses a mesoscale meteorological model coupled with a three-dimensional hydrodynamic and water quality model to conduct detailed numerical simulations. The study evaluates the effects of three water diversion operation scenarios and three subsurface flow guide dam scenarios during the ecological water replenishment period in Chaohu Lake from September to November. The simulation results indicate that all three water diversion operation scenarios improve the hydrodynamic conditions of Chaohu Lake, but there are significant differences in their effects on pollutant reduction in the lake. The retention of chemical oxygen demand (COD) in the water ranges from −36,812.1 to 472.8 tons, total nitrogen (TN) retention ranges from −22,637.2 to 3 tons, total phosphorus (TP) retention ranges from −4974 to 10.7 tons, and chlorophyll-a (Chl-a) retention ranges from −310.8 to −3.3 tons. Among the three subsurface flow guide dam schemes, all can promote the outflow of pollutants from Chaohu Lake. The combined subsurface flow guide dam scheme is the most effective, enabling an approximately 7.4% increase in pollutant export. The study demonstrates that diverting Huaihe River water through Paihe into Chaohu Lake, along with adding a combined subsurface flow guide dam in the West Lake area, can significantly improve the hydrodynamics and water quality in the West Lake area. This research provides essential technical support for the future operation of the Yangtze-to-Huaihe River Water Diversion Project and the layout of subsurface flow guide dams in Chaohu Lake, offering valuable insights for the ecological management of other shallow lakes. Full article

Climate challenges, along with a projected global population increase of 2 billion by 2080, are intensifying pressures on agricultural systems, leading to biodiversity loss, land use constrains, soil fertility declining, and changes in water cycles, while crop yields struggle to meet the rising food demand. These challenges, coupled with evolving legislation and rapid technology advancements, require innovative sustainable agricultural solutions. By reshaping farmers’ daily operations, real-time data acquisition and predictive models can support informed decision-making. In this context, smart farming (SM) applied to plant breeding can improve efficiency by reducing inputs and increasing outputs through the adoption of digital and data-driven technologies. Examples include the investment on common ontologies and metadata standards for phenotypes and environments, standardization of HTP protocols, integration of prediction outputs into breeding databases, and selection workflows, as well in building multi-partner field networks that collect diverse envirotypes. This review outlines how AI and machine learning (ML) can be integrated in modern plant breeding methodologies, including genomic selection (GS) and genetic algorithms (GAs), to accelerate the development of climate-resilient and sustainably performing crop varieties. While many reviews address smart farming or smart breeding independently, herein, these domains are bridged to provide an understandable strategic landscape by enhancing breeding efficiency. Full article

Groundwater resources are scarce in the cold and arid regions of north China. Moreover, regional water resource replenishment without external sources remains difficult. This water deficit has become a major factor restricting the sustainable development of regional vegetable production. The effective utilization of rainwater harvesting for irrigated agricultural production is necessary to suppress droughts and floods in farming under the semi-arid climate of this area in order to both guarantee a stable supply of vegetables to the market in south and north China and promote the balanced development of regional agriculture–resource–environment integration. In this study, based on continuous simulation and Python modeling, we simulated and analyzed the water supply and production effects of irrigation with harvests and stored rainwater on tomatoes under different water supply scenarios from 1992 to 2023. We then designed and tested a water-saving and high-yield project for rainwater-irrigated greenhouses in 2024 and 2025 under natural rainfall conditions in northwestern Hebei Province based on the reference irrigation scheme. The water supply satisfaction rate, water demand satisfaction rate, and volume of water inventory of tomato fields under different water supply scenarios increased with the rainwater tank size, and the corresponding drought yield reduction rate of tomato decreased. Under the actual rainfall scenarios in 2024 and 2025, a 480 m² greenhouse with a 14.4 m³ rainwater tank for producing tomatoes irrigated with rainwater drip from the greenhouse film collected 127.7 and 120.5 m³ of rainwater, respectively. The volume of the rainwater tank was exceeded 8.3 and 8.0 times, and up to 93.8% and 95.0% of the irrigated groundwater was replaced; additionally, the average yield of the small-fruited tomato ‘Beisi’ was 50,076.6 kg·hm⁻² and 48,110.2 kg·hm⁻², reaching 96.1% and 92.3% of the expected yield. Conclusion: The irrigation strategy based on the innovative “greenhouse film–rainwater harvesting–groundwater replenishment” model developed in this study has successfully achieved a high substitution rate of groundwater for greenhouse tomato production in the cold and arid regions of north China while ensuring stable yields by mitigating drought and waterlogging risks. This model not only provides a replicable technical framework for sustainable agricultural water resource management in semi-arid areas but also offers critical theoretical and practical support for addressing water scarcity and ensuring food security under global climate change. Full article

Freshwater resources are on the verge of depletion due to the rapid increase in population, lifestyle changes, and especially during climate change in Iraq. Therefore, treating domestic wastewater correctly will significantly contribute to keeping the balance of water purity and its usage. To fulfil this, the Sustainable Project Appraisal Routine (SPeAR^TM) program, which leverages Multi-Criteria Decision Analysis with operational sustainability indicators, is used to compare the relative sustainability performance of the novel Modified Sequencing Batch Reactor by visualising the results of the degree of its sustainability compared to the Moving Bed Biofilm Reactor and the conventional Sequencing Batch Reactor system. Although selecting the most sustainable treatment depends on specific treatment goals, available resources, site conditions, and stakeholder preferences, this study considers the equal weighting of sustainability assessment across environmental, social, and economic indices to inform sustainable decision making. The results show that integrating both conventional treatment plants into the novel modified treatment plant demonstrates a comparatively more balanced and stable sustainability performance under the assessed operational conditions. As at a design capacity of 100 m³·day⁻¹, the MSBR achieved a higher organic and nutrient removal efficiencies relative to the conventional SBR and MBBR systems while operating at an intermediate energy demand (187.7 kWh·day⁻¹) compared with the SBR (121.7 kWh·day⁻¹) and the MBBR (211.8 kWh·day⁻¹). Thus, it can compensate for the weaknesses and combines the strengths of the sustainability indices of the two systems, which supports the Modified Sequencing Batch Reactor as a comparatively favourable option for wastewater treatment within the assessed sustainability framework. Full article

Microplastics are very small particles of plastics, usually smaller than 5 mm. Microplastic pollution has emerged as a rising and challenging issue worldwide, posing serious threats to aquatic and terrestrial ecosystems and human health. Because of global demand and frequent use in daily routines, including clothing, packaging, and household items, the production of plastic is increasing annually. This study provides a comprehensive overview of the source, classification (based on shape, color, polymer), transportation, and impact of microplastic pollution. Depending upon size, mass, and density, microplastics can be transported to the environment via air and water. However, microplastics can be inhaled and ingested by humans, causing various health issues; for example, aquatic organisms like small fish ingest microplastics, which accumulate through the food chain and end up in the human body. This can lead to physiological harm, including inflammation, digestion tract obstruction, biomagnification throughout the food chain, and reproductive failure. This study further highlighted initiatives taken by government agencies to address plastic and microplastic pollution across India; for example, The Ministry of Environment Forest and Climate Change (MoEFCC) has formulated and amended the Plastic Waste Management (PWM) rules, Mission LiFE (LiFEStyle for Environment) launched campaigns such as “Say No to Single Use Plastic” and “One Nation, One Mission: End Plastic Pollution” to create awareness at the grassroot level, and institutions like the Food Safety and Standards Authority of India (FSSAI) have initiated a project to detect microplastics in food products. In addition, the National Green Tribunal (NGT) has instructed the Central Pollution Control Board (CPCB) to actively take measures to address microplastic pollution across Indian cities, focusing on key parameters like air, water, food, and humans. This study presents several recommendations, including detection and removal techniques (conventional, advanced, and removal); strengthening legislative policies such as Extended Producer Responsibility (EPR); research collaboration and monitoring with institutions such as CSIR-IITR, ICAR-CIFT, and BITS-Pilani; integrating EPR and Material Recovery Facilities (MRF) to develop a circular economy model; and mass awareness through government initiatives like the Swachh Bharat and Smart City programs to foster long-term behavioral change. Full article