Search Results (3,437)

Advancing Integrated Water Resources Management (IWRM) is essential for integrating land and water strategies and ensuring access to safe and secure water services. Yet, assessing the quality of IWRM implementation remains a persistent challenge for policy and practice. This study presents the first systematic review of 375 empirical articles to consolidate evidence on how enablers and obstacles shape IWRM’s effectiveness in advancing Sustainable Territorial Development (S-TD). Following PRISMA guidelines and combining bibliometric and qualitative coding procedures, we identify ten categories of enablers and eleven categories of obstacles. Results show that institutional strengthening, stakeholder participation, and technological innovation are the most frequent enablers, while fragmentation, coordination challenges, and financial limitations are the most prevalent obstacles. Beyond frequency patterns, this review highlights that outcomes depend on the configurations and interactions of these factors, which condition IWRM’s capacity to steer sustainable development trajectories in the territory. By comparing enablers and obstacles across nexus sectors (food, energy, land) and geographic scales (sub-basin, basin, transboundary, urban, national), we delineate scale- and sector-sensitive pathways linking IWRM to S-TD. To support further research, we provide an open-access dataset as a unique resource for replication, comparative analysis, and policy design, enabling evidence-based decision-making toward sustainability and resilience across diverse geographical and institutional contexts. Full article

Dew formation occurs frequently and in substantial amounts, serving as an important water source with significant ecological implications for plant growth. Although previous studies have demonstrated that dew can supplement leaf water, quantitative evidence of leaf dew absorption under different dew intensities remains limited. In this study, a stable isotope tracer experiment was conducted to quantify dew absorption under varying dew amounts and to analyze absorption rates and influencing factors across different plant species. Results showed that all four species were capable of absorbing dew, mainly due to specialized leaf surface morphology and microstructures. At a dew intensity of 0.1 mm, Tillandsia ionantha, whose leaves are densely covered with shield-like trichomes, exhibited an extremely high dew absorption rate of 92%. In contrast, the leaf surface of purple shamrock (Oxalis triangularis ‘Purpurea’) is covered with abundant hydrophobic trichomes that strongly restrict dew entry, resulting in a very low absorption rate of only 1.43%. Dew absorption varied markedly among species under different dew amounts. Under dew intensities of 0.1, 0.2, and 0.3 mm, T. ionantha showed consistently high absorption rates of 92%, 89.60%, and 71.74%, respectively, whereas Epipremnum aureum exhibited much lower rates of 3.72%, 6.15%, and 2.45%. Moreover, under a dew intensity of 0.2 mm, dew absorbed by E. aureum leaves could be transported to the roots, indicating internal redistribution of foliar-absorbed water. Overall, dew represents an important supplementary water source for plants, and interspecific differences in leaf surface morphology and microstructures lead to substantial variation in dew absorption capacity. These findings provide experimental evidence for understanding species-specific strategies of dew utilization and have implications for the efficient use of dew as a water resource. Full article

Background/Objectives: Contemporary food systems face dual imperatives of ensuring nutritional adequacy while minimizing environmental resource consumption, yet conventional dietary assessment methodologies inadequately integrate these competing objectives. This simulation-based proof-of-concept study developed an artificial intelligence-driven computational framework synthesizing nutritional evaluation, environmental footprint quantification, and economic accessibility assessment. Methods: The analytical architecture integrated random forest classification, dimensionality reduction, and scenario-based optimization across a simulated population cohort of 1500 individuals. Food composition data encompassed 55 representative foods across eight categories linked with greenhouse gas emissions, water use, and price parameters. Four dietary patterns (Mediterranean, Western, Plant-based, Mixed) were characterized across nutrient adequacy, greenhouse gas emissions, water consumption, and economic cost. Results: Random forest classification achieved 39.1% accuracy, with cost, greenhouse gas emissions, and water consumption emerging as the most discriminating features. Dietary patterns exhibited convergent macronutrient profiles (protein 108.8–112.8 g per day, 4% variation) despite categorical distinctions, while calcium inadequacy pervaded all patterns (867–927.5 mg per day, 7–13% below requirements). Environmental footprints demonstrated limited differentiation (greenhouse gas 3.73–3.96 kg CO₂e per day, 6% range). Bootstrap resampling (n = 1000) confirmed narrow confidence intervals, with NHANES validation revealing substantial energy intake deviations (38–58% above observed means) attributable to adequacy-prioritized design rather than observed consumption patterns. Scenario modeling identified seasonally flexible dietary configurations maintaining micronutrient and protein adequacy while reducing water use to 87% of baseline at modest cost increases. Conclusions: This framework establishes a validated computational infrastructure for integrated dietary assessment benchmarked against sustainability thresholds and epidemiological reference data, demonstrating the feasibility of AI-driven evaluation of dietary patterns across nutritional, environmental, and economic dimensions. Full article

Evapotranspiration (ET) links the water cycle with the energy balance and serves as a key driving process for ecosystem functioning and water resource management. Canopy conductance (Gc) plays a central role in regulating transpiration, but many models inadequately represent its regulatory mechanisms and show varying applicability across different land cover types. This study develops a remote-sensing ET estimation approach suitable for large scales and diverse land cover types and proposes an improved canopy conductance model for daily latent heat flux (LE) estimation. By integrating the canopy radiation transfer concept from the K95 model into the multiplicative Jarvis framework, an improved canopy conductance model is developed that includes limiting effects from photosynthetically active radiation (PAR), vapor pressure deficit (VPD), air temperature (T), and soil moisture (θ). Eighteen combinations of limiting functions are designed to evaluate structural performance differences. Using observations from 79 global flux sites during 2015–2023 and integrating multi-source datasets, including ERA5, MODIS, and SMAP, a two-stage parameter optimization was applied to determine the optimal limiting function combination for each land cover type. And nine sites from nine different land cover types were selected for independent spatial validation. Temporal validation within the optimization sites shows that, at the daily scale, the model achieves a Kling–Gupta efficiency (KGE) of 0.82, a correlation coefficient (R) of 0.82, and a Root Mean Square Error (RMSE) of 27.83 W/m², demonstrating strong temporal stability. Spatial validation over independent holdout sites achieved KGE = 0.84, R = 0.84, and RMSE = 22.53 W/m². At the 8-day scale, when evaluated over the holdout sites, the model achieves KGE = 0.87, R = 0.88, and RMSE = 18.74 W/m². Compared with the K95 and Jarvis models, KGE increases by about 34% and 15%, while RMSE decreases by about 38% and 12%, respectively. Relative to the MOD16 and PML-V2 products, KGE increases by about 32% and 16%, while RMSE decreases by about 33% and 17%, respectively. Comprehensive comparisons show that explicitly coupling canopy structure with multiple environmental constraints within the Jarvis framework, together with structure optimization across land cover types, can markedly improve large-scale remote-sensing ET retrieval accuracy while maintaining physical consistency and physiological rationality. This provides an effective pathway and parameterization scheme for producing ET products applicable across ecosystems. Full article

Climate change has led to increasingly frequent and unpredictable droughts and high-temperature events, creating extreme conditions that profoundly impact the productivity of freshwater ecosystems. In this study, we evaluated the effects of extreme temperature and drought events on Nanwan Reservoir, a large, deep body of water in Xinyang, China, by assessing water quality and phytoplankton biomass. Field investigations were conducted during both high-temperature and drought (HTD) conditions in 2019 and normal-temperature and non-drought (NTND) conditions in 2020. HTD conditions significantly disrupted the thermocline and oxycline structures, leading to prolonged stratification during this period. Although phosphorus concentrations remained relatively stable across both periods, nitrogen levels were markedly lower during HTD events, indicating a possible shift in nutrient limitation from phosphorus to nitrogen. Additionally, a complex relationship between environmental variables and phytoplankton biomass was observed under HTD conditions. These findings advance our understanding of primary production responses to extreme weather events in Nanwan Reservoir, highlighting the importance of incorporating this knowledge into water resource management and ecological conservation strategies. Full article

Aridity represents a fundamental climatic constraint governing water resources, ecosystem functioning, and agricultural systems in transitional climate zones. This study examines the spatial organization and temporal variability of aridity and thermal continentality in North Macedonia using observational records from 13 meteorological stations distributed across contrasting altitudinal and physiographic settings. The analysis is based on homogenized monthly and annual air temperature and precipitation series covering the period 1991–2020. Aridity and continentality were quantified using the Johansson Continentality Index (JCI), the De Martonne Aridity Index (I_DM), and the Pinna Combinative Index (I_P). Temporal consistency and trend behavior were evaluated using Pettitt’s nonparametric change-point test, linear regression, the Mann–Kendall test, and Sen’s slope estimator. Links between aridity variability and large-scale atmospheric circulation were examined using correlations with the North Atlantic Oscillation (NAO) and the Southern Oscillation Index (SOI). The results show a spatially consistent and statistically significant increase in mean annual air temperature, with a common change point around 2006, while precipitation displays strong spatial variability and limited temporal coherence. Aridity patterns display a strong altitudinal control, with extremely humid to very humid conditions prevailing in mountainous western regions and semi-humid to semi-dry conditions dominating lowland and southeastern areas, particularly during summer. Trend analyses do not reveal statistically significant long-term changes in aridity or continentality over the study period, although low-elevation stations exhibit weak drying tendencies. A moderate positive association between I_DM and I_P (r = 0.66) confirms internal consistency among aridity indices, while summer aridity shows a statistically significant relationship with the NAO. These results provide a robust climatic reference for North Macedonia, establishing a first climatological baseline of aridity conditions based on multiple indices applied to homogenized observations, and contributing to regional assessments of hydroclimatic variability relevant to climate adaptation planning. Full article

Groundwater is a critical resource for agriculture and livelihoods, particularly in semi-arid regions such as Gujarat and Rajasthan in India. However, unsustainable extraction has led to aquifer depletion and increased water insecurity. This study uses Ostrom’s design principles to evaluate how Village Groundwater Cooperatives (VGCs) are transitioning toward self-governance in managing groundwater commons. Through field research in Dharta (Rajasthan) and Meghraj (Gujarat), including 33 key informant interviews and nine focus group discussions, this study assesses institutional robustness, rule enforcement, and community participation. Findings reveal that VGCs have the potential to enhance groundwater security through collective water budgeting and recharge interventions, though institutional robustness is constrained by limited formal enforcement. In Hinta, pipelines connected four wells to distribute water equitably, while in Dharta and Meghraj, traditional water-sharing agreements (two-part and three-part systems) sustained cooperation. Groundwater monitoring by trained “Bhujal Jankaars” helped farmers plan crop cycles, supporting informed crop choices that better aligned with available water supply. Despite these successes, to strengthen VGCs for effective groundwater management, formal sanctioning mechanisms are needed to address rule violations. Additionally, women’s participation in groundwater management decisions and operationalising VGCs is low. Conflict resolution mechanisms are currently informal. This study suggests that because women primarily manage domestic water needs while men manage irrigation, integrating women into decision-making is essential to reconcile competing water demands and ensure the long-term viability of VGCs. The findings provide policy insights for scaling up community-led groundwater governance in semi-arid regions. Full article

Green roofs in Southern Europe are interest-growing nature-based solutions, capable of improving urban sustainability by positively impacting the water cycle, biodiversity, pollution, and, in some cases, energy consumption and carbon sequestration. Native plants adapted to Mediterranean climates exhibit drought-resistant traits, making them highly suitable for the challenging microclimate of green roofs. This microclimate features intense solar radiation, strong winds, and higher temperatures, in comparison to ground level, leading to increased atmospheric evaporative demand, driven by the interplay of radiation, wind, temperature, and humidity. Consequently, native plants from ecosystems resembling this microclimate are likely better suited for green roofs than local ground-level species. The current review synthesizes current knowledge on the use of native plants in Southern European green roofs, focusing on water management challenges given the region’s climate and scarce water resources. Out of roughly 12,500 native plant species in the Mediterranean basin, only about 124 have been examined in the past 20 years for green roof applications, with just 16% appearing in multiple scientific studies, highlighting a significant knowledge gap. The data indicate that ca. 85% of these species are perennials, valued for their low maintenance needs, a key consideration for green roof sustainability. Some of the studied species retain adequate aesthetic value when cultivated on green roofs with limited water availability. These species are mainly associated with four habitat types—rocky, coastal, dry, or well-drained environments—with a few linked to humid or adaptable conditions. This study aims to document the selection of drought-adapted native plant species best suited for green roof implementation in Southern Europe, contributing to enhancing sustainable urban design in the region, considering water management best practices and water use efficiency. Full article

Under intensifying climate change and anthropogenic pressures, extreme low-flow events increasingly jeopardize water security in the Yellow River water supply region. This study develops the Inter-basin Multi-source Water Joint Allocation and Interconnected Routes Regulation System (IMWA-IRRS) to optimize spatiotemporal allocation of multi-source water and simulate topological relationships in complex water networks. The model integrates system dynamics simulation with multi-objective optimization, validated through multi-criteria calibration using three performance indicators: correlation coefficient (R), Nash-Sutcliffe Efficiency (E_ns), and percent bias (PBIAS). Application results demonstrated exceptional predictive performance in the study area: Monthly runoff simulations at four hydrological stations yielded R > 0.98 and E_ns > 0.98 between simulated and observed data during both calibration and validation periods, with |PBIAS| < 10%; human-impacted runoff simulations at four hydrological stations achieved R > 0.8 between simulated and observed values, accompanied by PBIAS within ±10%; sectoral water consumption across the Yellow River Basin exhibited PBIAS < 5%, while source-specific water supply simulations maintained PBIAS generally within 10%. Comparative analysis revealed the IMWA-IRRS model achieves simulation performance comparable to the WEAP model for natural runoff, human-impacted runoff, water consumption, and water supply dynamics in the Yellow River Basin. The 2035 water allocation scheme for Yellow River water supply region projects total water supply of 59.691 billion m³ with an unmet water demand of 3.462 billion m³ under 75% low-flow conditions and 58.746 billion m³ with 4.407 billion m³ unmet demand under 95% low-flow conditions. Limited coverage of the South-to-North Water Diversion Project’s Middle and Eastern Routes constrains water supply security, necessitating future expansion of their service areas to leverage inter-route complementarity while implementing demand-side management strategies. Collectively, the IMWA-IRRS model provides a robust decision-support tool for refined water resources management in complex inter-basin diversion systems. Full article

Water is a critical resource underpinning natural, societal and economic development, and its importance will grow bigger in the next decades. Interfacial solar evaporators are a promising and cost-effective technology for the generation of freshwater from saline and polluted waters. Yet, although these devices effectively reject salts and non-volatile pollutants, the presence of volatile organic compounds in the water source may lead to low water quality of the distillate. This review addresses the introduction of photocatalytic materials in solar evaporator devices to improve water quality, highlighting in particular possible synergies and incompatibilities between the materials promoting these functionalities. The interactions of the photocatalyst with photothermal materials are described, along with an overview of the materials most commonly selected for both functionalities. A positive interaction clearly emerges, with the photothermal materials not only accelerating evaporation but also generally stimulating the photocatalytic degradation of VOCs. Limits to the implementation of such a combination are described, including those due to electrolyte content and salt accumulation, reaction rate and mass transfer. Finally, recommendations regarding testing conditions and future studies are presented. Full article

The agri-food sector is a major contributor to global greenhouse gas emissions while facing increasing demand for food production driven by population growth. Transitioning towards sustainable and low-carbon agricultural systems is therefore critical. Green hydrogen, produced from renewable energy sources, holds significant promise as a clean energy carrier and chemical feedstock to decarbonize multiple stages of the agri-food supply chain. This systematic review is based on a structured analysis of peer-reviewed literature retrieved from Web of Science, Scopus, and Google Scholar, covering over 120 academic publications published between 2010 and 2025. This review provides a comprehensive overview of hydrogen’s current and prospective applications across agriculture and the food industry, highlighting opportunities to reduce fossil fuel dependence and greenhouse gas emissions. In agriculture, hydrogen-powered machinery, hydrogen-rich water treatments for crop enhancement, and the use of green hydrogen for sustainable fertilizer production are explored. Innovative waste-to-hydrogen strategies contribute to circular resource utilization within farming systems. In the food industry, hydrogen supports fat hydrogenation and modified atmosphere packaging to extend product shelf life and serves as a sustainable energy source for processing operations. The analysis indicates that near-term opportunities for green hydrogen deployment are concentrated in fertilizer production, food processing, and controlled-environment agriculture, while broader adoption in agricultural machinery remains constrained by cost, storage, and infrastructure limitations. Challenges such as scalability, economic viability, and infrastructure development are also discussed. Future research should prioritize field-scale demonstrations, technology-specific life-cycle and techno-economic assessments, and policy frameworks adapted to decentralized and rural agri-food contexts. The integration of hydrogen technologies offers a promising pathway to achieve carbon-neutral, resilient, and efficient agri-food systems that align with global sustainability goals and climate commitments. Full article

Rigid polyurethane (PUR) foams are widely used across multiple industries due to their excellent thermal insulation and mechanical properties. However, their environmental impact, flammability, and limited thermal stability pose challenges for sustainable development. In this study, selected natural minerals—including talc, montmorillonite, halloysite, and diatomite—were incorporated into water-blown polyurethane foams to improve their performance while enhancing sustainability. The prepared foams were characterized in terms of apparent density, water uptake, compressive strength, dimensional stability, and thermal and fire resistance. The results indicate that the inclusion of mineral additives significantly improves the physical and mechanical properties of polyurethane foams, increasing durability, resistance to high temperatures, and fire safety. By using naturally occurring minerals, the study promotes the development of polyurethane foams with reduced environmental footprint, longer service life, and safer application potential in construction, automotive, and heating systems. These findings highlight the contribution of mineral-reinforced polyurethane foams to sustainable materials engineering and resource-efficient industrial applications. Full article

Understanding the behavior of light non-aqueous phase liquids (LNAPLs) in urban subsurface environments is essential to developing effective pollution control strategies, designing remediation systems, and managing waste and resources sustainably. Oil leakage from urban industrial facilities, underground pipelines, and fueling systems often leads to contamination that is challenging to characterize due to complex soil structures, limited access beneath densely built infrastructure, and dynamic groundwater conditions. In this study, we integrate a large-scale soil tank experiment with multiphase flow simulations to elucidate LNAPL distribution mechanisms under fluctuating groundwater conditions. A 2.4-m-by-2.4-m-by-0.6-m soil tank was used to visualize oil movement with high-resolution multispectral imaging, enabling a quantitative evaluation of saturation distribution over time. The results showed that a rapid rise in groundwater can trap 60–70% of the high-saturation LNAPL below the water table. In contrast, a subsequent slow rise leaves 10–20% residual saturation within pore spaces. These results suggest that vertical redistribution caused by groundwater oscillation significantly increases residual contamination, which cannot be evaluated using static groundwater assumptions. Comparisons with a commonly used NAPL simulator revealed that conventional models overestimate lateral spreading and underestimate trapped residual oil, thus highlighting the need for improved constitutive models and numerical schemes that can capture sharp saturation fronts. These results emphasize that an accurate assessment of LNAPL contamination in urban settings requires an explicit consideration of groundwater fluctuation and dynamic multiphase interactions. Insights from this study support rational monitoring network design, reduce uncertainty in remediation planning, and contribute to sustainable urban environmental management by improving risk evaluation and preventing the long-term spread of pollution. Full article

Water resources are of critical importance across all ecological, social, and economic realms. Accurate extraction of water bodies is of significance to estimate the spatial coverage of water resources and to mitigate water-related disasters. Single-modal remote sensing images are often insufficient for accurate water body extraction due to limitations in spectral information, weather conditions, and speckle noises. Furthermore, state-of-the-art deep learning models may be constrained by data extensibility, feature transferability, model scalability, and task producibility. This manuscript presents an integrated GeoAI framework that enhances foundation models for efficient water body extraction with multi-modal remote sensing images. The proposed framework consists of a data augmentation module tailored for optical and synthetic aperture radar (SAR) remote sensing images, as well as extraction modules augmented by three popular foundation models, namely SAM, SAMRS, and CROMA. Specifically, optical and SAR images are preprocessed and augmented independently, encoded through foundation model backbones, and subsequently decoded to generate water body segmentation masks under single-modal and multi-modal settings. Full article

Long-term continuous cropping in cotton fields of Southern Xinjiang has limited crop productivity. To investigate how subsoiling depth regulates ecosystem-level water partitioning and thereby enhances water productivity mechanisms, a two-year field experiment was conducted in a mulched drip irrigation cotton field in Southern Xinjiang. Using a non-subsoiled field in the current season (CT) as the control, three subsoiling depths were established: subsoiling at 30 cm (ST1), 40 cm (ST2), and 50 cm (ST3). Changes in evapotranspiration partitioning and water use efficiency were analyzed. The results showed that subsoiling enhanced the utilization of deep soil water. Compared with CT, the ST2 and ST3 treatments significantly reduced soil water storage in the 0–60 cm layer during the flower opening to boll-setting stages, while soil water consumption increased by 26.4 mm and 28.8 mm, respectively. We demonstrate that subsoiling depth exerts a predominant control on the partitioning of evapotranspiration. Increasing subsoiling depth systematically shifted water loss from non-productive soil evaporation to productive plant transpiration, with the ST2 and ST3 treatments decreasing seasonal soil evaporation by 24.1% and 25.1%, respectively, and increasing plant transpiration by 21.9% and 22.8%, and lowering the Es/ET (where Es is soil evaporation and ET is evapotranspiration) ratio by 22.1% and 27.1%. However, this maximal physiological water-saving did not yield the optimal agronomic return. We established a non-linear relationship in which the ST2 treatment uniquely achieved the maximum seed cotton yield, WUE (water use efficiency), and IWUE (irrigation water use efficiency) (increasing by up to 34.4%, 17.2%, and 23.4%, respectively). This optimal depth better balances water resource allocation and reproductive growth. We conclude that under sandy loam soil conditions in typical mulched drip-irrigated cotton areas of Southern Xinjiang, implementing an optimal subsoiling depth (40 cm) can engineer a more resilient soil–plant–water continuum, providing a feasible pathway toward enhancing water and crop production sustainability. Full article