Search Results (427)

This study was developed to identify the optimal (most cost-effective) strategies to reduce sediment and phosphorus loadings in the Upper Soldier Creek, Kansas, USA, watershed using the Watershed Management Optimization Support Tool (WMOST) suite of programs. Under average precipitation, loading targets for upland total phosphorus (TP) could be met with use of grassed swales for treating urban area runoff and of contouring for agricultural runoff. For a wet year, the same target could be met, but with use of a sand filter with underdrain for the urban runoff. Both annual and daily TP loading targets from Total Maximum Daily Loads (TMDLs) were exceeded in simulations of best management practice (BMP) solutions for 14 alternative future climate scenarios. We expanded the set of BMPs to include stream bank stabilization (physical plus riparian restoration) and two-stage channel designs, but upland loading targets could not be met for either TP or total suspended solids (TSS) under any precipitation conditions. An optimization scenario that simulated the routing of flows in excess of those treated by the upland BMPs to an off-channel treatment wetland allowed TMDLs to be met for an average precipitation year. WMOST can optimize cost-effectiveness of BMPs across multiple scales and climate scenarios. Full article

The scientific literature currently lacks studies that evaluate the nutritional composition of the tissues of cattle raised in different systems, so that the nutritional effects can be known and used to enhance consumption and use in the diet. The aim was therefore to assess whether the mineral content of muscle tissue (longissimus lumborum) in cattle finished during the rainy season in the Eastern Amazon is influenced by different farming systems. The treatments consisted of four systems (three pasture production systems and one feedlot system). 1. native wetland pasture in Santa Cruz do Arari (Mesoregion of Marajó); 2. native wetland pasture in Monte Alegre (Mesoregion of Baixo Amazonas); 3. cultivated dryland pasture in São Miguel do Guamá (Mesoregion of Nordeste Paraense); and 4. Confinement in Santa Izabel do Pará (Metropolitan Region of Belém). The analyses were carried out on samples of the longissimus lumborum muscle tissue of 48 male, castrated, crossbred Nelore cattle, twelve per breeding system, from commercial farms, destined for meat production, finished during the rainiest period of the year (between January and June). In systems 1 and 2, the animals were slaughtered in licensed slaughterhouses; the animals in systems 3 and 4 were slaughtered in commercial slaughterhouses. Food sampling and chemical analysis, soil sample collection and analysis, longissimus lumborum muscle tissue collection, sample preparation and digestion, and inductively coupled plasma optical emission spectrometry were evaluated. The experimental design was completely randomized in a linear model with four rearing systems and one period (rainy). The data was compared using the Statistical Analysis Systems (SAS) program. All analyses were carried out considering a significance level of 0.05. Samples of the diets offered (pasture and concentrate) were also collected. The Amazon systems influenced the macro- and micromineral content in the muscles of cattle (p < 0.05). The interaction between pasture systems vs. confinement showed differences in the minerals calcium (Ca), magnesium (Mg), phosphorus (P), copper (Cu), zinc (Zn), iron (Fe), and manganese (Mn) (p < 0.05). However, there was no difference in the values of sodium (Na), potassium (K), and sulfur (S) between the rearing systems (p > 0.05). By contrast, the cultivated pasture system vs. extensive pasture showed differences in all the elements evaluated (p < 0.05). The rearing systems of the Eastern Amazon influenced the mineral content of beef, which continues to be an excellent source of macro- and microminerals and can compose the human diet. Full article

Various nature-based solutions (NbS)—such as constructed wetlands, drainage ditches, and vegetated buffer strips—have recently demonstrated strong potential for mitigating pollutant transport in open channels and river systems. Numerical modeling is a widely adopted and effective approach for assessing the performance of these interventions. This study presents the first development of a two-dimensional (2D) meshless advection–diffusion model based on an Eulerian smoothed particle hydrodynamics (SPH) framework, specifically designed to simulate passive pollutant transport in open channel flows. The proposed model marks a pioneering application of the ESPH technique to environmental pollutant transport problems. It couples the 2D depth-averaged shallow water equations with an advection–diffusion equation to represent both fluid motion and pollutant concentration dynamics. A uniform particle arrangement ensures that each fluid particle interacts symmetrically with eight neighboring particles for flux computation. To represent the pollutant transport process, the dispersion coefficient is defined as the sum of molecular and turbulent diffusion components. The turbulent diffusion coefficient is calculated using a prescribed turbulent Schmidt number and the eddy viscosity obtained from a Smagorinsky-type mixing-length turbulence model. Three analytical case studies, including one-dimensional transcritical open channel flow, 2D isotropic and anisotropic diffusion in still water, and advection–diffusion in a 2D uniform flow, are employed to verify the model’s accuracy and convergence. The model demonstrates first-order convergence, with relative root mean square errors (RRMSEs) of approximately 0.2% for water depth and velocity, and 0.1–0.5% for concentration. Additionally, the model is applied to a laboratory experiment involving 2D pollutant dispersion in a 90° junction channel. The simulated results show good agreement with measured velocity and concentration distributions. These findings indicate that the developed model is a reliable and effective tool for evaluating the performance of NbS in mitigating pollutant transport in open channels and river systems. Full article

Lake Chinchaycocha, Peru’s second-largest high-altitude lake and a Ramsar-designated wetland of international importance, is increasingly threatened by anthropogenic pollution and hydroclimatic shifts. This study integrates Sentinel-2 multispectral imagery with in situ water quality data from Peru’s National Water Observatory to assess spatiotemporal dynamics in 31 physicochemical parameters between 2018 and 2024. We evaluated 40 empirical algorithms developed globally for Sentinel-2 and tested their transferability to this ultraoligotrophic Andean system. The results revealed limited predictive accuracy, underscoring the need for localized calibration. Subsequently, we developed and validated site-specific models for ammoniacal nitrogen, electrical conductivity, major ions, and trace metals, achieving high predictive performance during the rainy season (R² up to 0.95). Notably, the study identifies consistent seasonal correlations—such as between total copper and ammoniacal nitrogen—and strong spectral responses in Band 1, linked to runoff dynamics. These findings highlight the potential of combining public monitoring data with remote sensing to enable scalable, cost-effective assessment of water quality in optically complex, high-Andean lakes. The study provides a replicable framework for integrating national datasets into operational monitoring and environmental policy. Full article

The transition toward a circular water economy addresses accelerating water scarcity and pollution. A PRISMA-2020 systematic review of 50 peer-reviewed articles (January 2018–April 2024) mapped current technologies and management strategies, seeking patterns, barriers, and critical bottlenecks. Bibliometric analysis revealed the following three dominant patterns: (i) rapid diffusion of membrane bioreactors, constructed wetlands, and advanced oxidation processes; (ii) research geographically concentrated in Asia and the European Union; (iii) industry’s marked preference for by-product valorization. Key barriers—high energy costs, fragmented regulatory frameworks, and low social acceptance—converge as critical constraints during scale-up. The following three practical action lines emerge: (1) adopt progressive tariffs and targeted tax credits that internalize environmental externalities; (2) harmonize water-reuse regulations with comparable circularity metrics; (3) create multi-actor platforms that co-design projects, boosting local legitimacy. These findings provide policymakers and water-sector practitioners with a clear roadmap for accelerating Sustainable Development Goals 6, 9, and 12 through circular, inclusive, low-carbon water systems. Full article

Groundwater systems are intrinsically linked to climate, with changing conditions significantly altering recharge, storage, and discharge processes, thereby impacting water availability and ecosystem integrity. Critical knowledge gaps persist regarding groundwater equilibrium timescales, water table dynamics, and their governing factors. This study develops a novel remote sensing framework to quantify factor controls on groundwater–climate interaction characteristics in the Heihe River Basin (HRB). High-resolution (0.005° × 0.005°) maps of groundwater response time (GRT) and water table ratio (WTR) were generated using multi-source geospatial data. Employing Geographical Convergent Cross Mapping (GCCM), we established causal relationships between GRT/WTR and their drivers, identifying key influences on groundwater dynamics. Generalized Additive Models (GAM) further quantified the relative contributions of climatic (precipitation, temperature), topographic (DEM, TWI), geologic (hydraulic conductivity, porosity, vadose zone thickness), and vegetative (NDVI, root depth, soil water) factors to GRT/WTR variability. Results indicate an average GRT of ~6.5 × 10⁸ years, with 7.36% of HRB exhibiting sub-century response times and 85.23% exceeding 1000 years. Recharge control dominates shrublands, wetlands, and croplands (WTR < 1), while topography control prevails in forests and barelands (WTR > 1). Key factors collectively explain 86.7% (GRT) and 75.9% (WTR) of observed variance, with spatial GRT variability driven primarily by hydraulic conductivity (34.3%), vadose zone thickness (13.5%), and precipitation (10.8%), while WTR variation is controlled by vadose zone thickness (19.2%), topographic wetness index (16.0%), and temperature (9.6%). These findings provide a scientifically rigorous basis for prioritizing groundwater conservation zones and designing climate-resilient water management policies in arid endorheic basins, with our high-resolution causal attribution framework offering transferable methodologies for global groundwater vulnerability assessments. Full article

Aquatic fungi serve as core ecological engines in freshwater ecosystems, driving organic matter decomposition and energy flow to sustain environmental balance. Wetlands, with their distinct hydrological dynamics and nutrient-rich matrices, serve as critical habitats for these microorganisms. As an internationally designated Ramsar Site, Yunnan Dashanbao Black-Necked Crane National Nature Reserve in China not only sustains endangered black-necked cranes but also harbors a cryptic reservoir of aquatic fungi within its peat marshes and alpine lakes. This study employed high-throughput sequencing to characterize fungal diversity and community structure across 12 understudied wetland sites in the reserve, while analyzing key environmental parameters (dissolved oxygen, pH, total nitrogen, and total phosphorus). A total of 5829 fungal operational taxonomic units (OTUs) spanning 649 genera and 15 phyla were identified, with Tausonia (4.17%) and Cladosporium (1.89%) as dominant genera. Environmental correlations revealed 19 genera significantly linked to abiotic factors. FUNGuild functional profiling highlighted saprotrophs (organic decomposers) and pathogens as predominant trophic guilds. Saprotrophs exhibited strong associations with pH, total nitrogen, and phosphorus, whereas pathogens correlated primarily with pH. These findings unveil the hidden diversity and ecological roles of aquatic fungi in alpine wetlands, emphasizing their sensitivity to environmental gradients. By establishing baseline data on fungal community dynamics, this work advances the understanding of wetland microbial ecology and informs conservation strategies for Ramsar sites. Full article

As power grids scale and aging assets edge toward obsolescence, grounding grid corrosion has become a critical vulnerability. Conventional diagnosis must fit high-dimensional electrical data to a physical model, typically yielding a nonlinear under-determined system fraught with computational burden and uncertainty. We propose the Enhanced Biomimetic Hippopotamus Optimization (EBOHO) algorithm, which distills the river-dwelling hippo’s ecological wisdom into three synergistic strategies: a beta-function herd seeding that replicates the genetic diversity of juvenile hippos diffusing through wetlands, an elite–mean cooperative foraging rule that echoes the way dominant bulls steer the herd toward nutrient-rich pastures, and a lens imaging opposition maneuver inspired by moonlit water reflections that spawn mirror candidates to avert premature convergence. Benchmarks on the CEC 2017 suite and four classical design problems show EBOHO’s superior global search, robustness, and convergence speed over numerous state-of-the-art meta-heuristics, including prior hippo variants. An industrial case study on grounding grid corrosion further confirms that EBOHO swiftly resolves the under-determined equations and pinpoints corrosion sites with high precision, underscoring its promise as a nature-inspired diagnostic engine for aging power system infrastructure. Full article

The U.S. Environmental Protection Agency (EPA) developed the concept of Water Quality Volume (WQv) as a Best Management Practice (BMP) to treat the first 25.4 mm of rainfall in urban areas, aiming to capture approximately 90% of annual runoff. However, applying this urban-based standard—designed for areas with over 50% imperviousness—to rural regions with higher infiltration and pervious surfaces may result in overestimated facility capacities. In Korea, a uniform WQv criterion of 5 mm is applied nationwide, regardless of land use or hydrological conditions. This study examines the suitability of this 5 mm standard in rural catchments using the Hydrological Simulation Program–Fortran (HSPF). Eight sub-watersheds in the target area were simulated under varying cumulative runoff depths (1–10 mm) to assess pollutant loads and runoff characteristics. First-flush effects were most evident below 5 mm, with variation depending on land cover. Nature-based treatment systems for constructed wetlands were modeled for each sub-watershed, and their effectiveness was evaluated using Flow Duration Curves (FDCs) and Load Duration Curves (LDCs). The findings suggest that the uniform 5 mm WQv criterion may result in overdesign in rural watersheds and highlight the need for region-specific standards that consider local land-use and hydrological variability. Full article

This study systematically compares the environmental and economic performance of three wastewater treatment systems: constructed wetlands (CWs), microbial fuel cells (MFCs), and their integration (CW–MFC). Lab-scale units of each system were constructed using a multi-media matrix (gravel, zeolite, and granular activated carbon), composite native wetland species (Juncus effusus, Iris sp., and Typha angustifolia), carbon-based electrodes (graphite), and standard inoculum for CW and CW–MFC. The MFC system employed carbon-based electrodes and proton-exchange membrane. The experimental design included a parallel operation of all systems treating domestic wastewater under identical hydraulic and organic loading rates. Environmental impacts were quantified across construction and operational phases using life cycle assessment (LCA) with GaBi software 9.2, employing TRACI 2021 and ReCiPe 2016 methods, while techno-economic analysis (TEA) evaluated capital and operational costs. The key results indicate that CW demonstrates the lowest global warming potential (142.26 kg CO₂-eq) due to its reliance on natural biological processes. The integrated CW–MFC system achieved enhanced pollutant removal (82.8%, 87.13%, 78.13%, and 90.3% for COD, NO₃, TN, and TP) and bioenergy generation of 2.68 kWh, balancing environmental benefits with superior treatment efficiency. In contrast, the stand-alone MFC shows higher environmental burdens, primarily due to energy-intensive material requirements and fabrication processes. TEA results highlight CW as the most cost-effective solution (USD 627/m³), with CW–MFC emerging as a competitive alternative when considering environmental benefits and operational efficiencies (USD 718/m³). This study highlights the potential of hybrid systems, such as CW–MFC, to advance sustainable wastewater treatment technologies by minimizing environmental impacts and enhancing resource recovery, supporting their broader adoption in future water management strategies. Future research should focus on optimizing materials and energy use to improve scalability and feasibility. Full article

The latest FAO report indicates that aquaculture accounts for 51% of the global production volume of fish and seafood. However, despite the continuous growth of this activity, there is evidence of the excessive use of groundwater in its production processes, as well as pollution caused by nutrient discharges into surface waters due to the water exchange required to maintain water quality in fishponds. Given this context, the objectives of this study were as follows: (1) to review which emergent and floating plant species are used in constructed wetlands (CWs) for the bioremediation of aquaculture wastewater; (2) to identify the aquaculture species whose wastewater has been treated with CW systems; and (3) to examine the integration of CWs with recirculating aquaculture systems (RASs) for water reuse. A systematic literature review was conducted, selecting 70 scientific articles published between 2003 and 2023. The results show that the most used plant species in CW systems were Phragmites australis, Typha latifolia, Canna indica, Eichhornia crassipes, and Arundo donax, out of a total of 43 identified species. These plants treated wastewater generated by 25 aquaculture species, including Oreochromis niloticus, Litopenaeus vannamei, Ictalurus punctatus, Clarias gariepinus, Tachysurus fulvidraco, and Cyprinus carpio, However, only 40% of the reviewed studies addressed aspects related to the incorporation of RAS elements in their designs. In conclusion, the use of plants for wastewater treatment in CW systems is feasible; however, its application remains largely at the experimental scale. Evidence indicates that there are limited real-scale applications and few studies focused on the reuse of treated water for agricultural purposes. This highlights the need for future research aimed at production systems that integrate circular economy principles in this sector, through RAS–CW systems. Additionally, there is a wide variety of plant species that remain unexplored for these purposes. Full article

Evaluating the environmental perception of urban parks is highly significant for optimizing urban planning. To address the limitations of traditional evaluation methods, a multimodal deep learning framework that integrates pre-training and reinforcement learning strategies for the comprehensive assessment of various park types (seaside, urban, mountain, and wetland) across three dimensions—accessibility, usability, and aesthetics—is proposed herein. By combining image data and user review texts, a unified architecture is constructed, including a text encoder, image visual encoder, and multimodal fusion module. During the pre-training phase, the model captured latent features in images and texts through a self-supervised learning strategy. In the subsequent training phase, a reinforcement learning strategy was introduced to optimize the sample selection and modal fusion paths to enhance the model’s generalization capability. To validate the cross-type prediction ability of the model, the experimental design uses data from three types of parks for training, with the remaining type as a test set. Results demonstrate that the proposed method outperforms LSTM and CNN architectures across accuracy, precision, recall, and F1 Score metrics. Compared with CNN, the proposed method improves accuracy by 5.1% and F1 Score by 6.6%. Further analysis shows that pre-training enhances the robust fusion of visual and textual features, while reinforcement learning optimizes the sample selection and feature fusion strategies during training. Full article

This study investigated the mechanisms determining macrophyte species composition in 23 Andalusian Mediterranean mountain wetlands (southern Spain). We employed a methodology combining two approaches: a pattern-based approach utilizing Elements of Metacommunity Structure (EMS) and a mechanistic approach involving Redundancy Analysis (RDA) and variance partitioning. This allowed us to identify the relevance of interactions between environmental and spatial factors. Data collection in these wetlands included macrophyte samples and physicochemical variables, alongside spatial variables generated using Moran’s Eigenvector Maps (MEMs). To refine the analysis of metacommunity structuring, the species matrix was partitioned based on macrophyte dispersal strategy (charophytes by spores and macrophyte vascular plants by seeds). Our results reveal that the macrophyte metacommunity in these wetlands exhibits quasi-clumped species loss for the total community, while charophytes and vascular plants showed quasi-random species loss. In conclusion, this study demonstrates that macrophyte communities in Mediterranean mountain wetlands do not follow a simple species replacement pattern. Instead, they are organized in a quasi-nested pattern, strongly shaped by environmental filters and, to a lesser extent, by spatial connectivity, with a prominent role for random processes. Understanding these mechanisms is crucial for predicting species responses to environmental changes and for designing effective conservation strategies within these vulnerable ecosystems. Full article

Methane (CH₄) emissions from dairy farming represent a substantial yet under-quantified share of agricultural greenhouse gas emissions. This study provides an in-depth, satellite-based fingerprinting analysis of methane emissions from Canada’s dairy sector, using Sentinel-5P/TROPOMI data. We utilized a robust quasi-experimental design, pairing 14 dairy-intensive zones with eight non-dairy reference regions, to analyze methane emissions from 2019 to 2024. A dynamic, region-specific baseline approach was implemented to remove temporal non-stationarity and isolate dairy-specific methane signals. Dairy regions exhibited consistently higher methane concentrations than reference areas, with an average methane anomaly of 17.4 ppb. However, this concentration gap between dairy and non-dairy regions notably narrowed by 57.23% (from 24.42 ppb in 2019 to 10.44 ppb in 2024), driven primarily by accelerated methane increases in non-dairy landscapes and a pronounced one-year contraction during 2022–2023 (−39.29%). Nationally, atmospheric methane levels rose by 3.83%, revealing significant spatial heterogeneity across provinces. Notably, an inverse relationship between the initial methane concentrations in 2019 and subsequent growth rates emerged, indicating spatial convergence. The seasonal analysis uncovered consistent spring minima and fall–winter maxima across regions, reflecting the combined effects of seasonal livestock management practices, atmospheric transport dynamics, and biogeochemical processes. The diminishing dairy methane anomaly suggests complex interplay of intensifying background methane emissions from climate-driven wetland fluxes, increasing fossil fuel extraction activities, and diffuse agricultural emissions. These findings underscore the emerging challenges in attributing sector-specific methane emissions accurately from satellite observations, highlighting both the capabilities and limitations of current satellite monitoring approaches. Full article

Plant diversity, as a critical indicator of wetland ecosystem health and functionality, has garnered extensive research attention. However, systematic and quantitative assessments of research advancements in wetland plant diversity remain inadequate. This study pioneers a global bibliometric analysis of wetland plant diversity research (1986–2025), designed to systematically examine its worldwide patterns, knowledge architecture, and evolutionary trends. Bibliometric analysis was performed using CiteSpace V6.2.R4 (64-bit) software on 482 publications retrieved from the Web of Science Core Collection. Results indicate that the United States, Canada, China, and several European countries have collectively prioritized wetland plant diversity research, forming a close international collaboration network. Research themes initially centered on species composition, community structure, and diversity metrics have expanded to multiple dimensions such as ecosystem functions and services, environmental change impacts, and wetland management and restoration, forming several key research clusters. Keyword time-zone mapping reveals the trajectory of research themes from basic descriptions to applied and environmental relevance, while emergent analyses accurately identify hotspots and frontiers of current research such as ecosystem services, functional diversity, and climate change impacts. These findings contribute to comprehending the overall framework and developmental trajectories in wetland plant diversity research, and provide a reference for identifying potential research gaps and planning future research directions. Full article