Surface Water Research Articles

Analysis of Water Film Distribution and Aerodynamic Performances of High-Speed Train Under Rainfall Environment

AbstractThe current research on the aerodynamic performance of the train running in rainy weather is primarily concerned with the trajectory of the raindrops and the aerodynamic variation of trains caused by raindrops. In fact, water film will generate on the train body when raindrops hit the train, which interacts with the flow field around the train, and would probably affect the aerodynamic performance of the train. In this paper, based on shear stress transport (SST) k-w turbulence model and Euler-Lagrange discrete phase model, the aerodynamic calculation model of a high-speed train under rainfall environment is established. The LWF (Lagrangian wall film) is used to simulate the water film distribution of the high-speed train under different rainfall intensities, and the aerodynamic performance of the train are studied. The calculation results show that raindrops will gather on the train surface and form water film under rainfall environment. With the extension of rainfall time, the thickness and coverage range of water film expand, and the maximum thickness of water film can reach 4.95 mm under the working conditions in this paper. The average thickness of water film on the train body increases with the rainfall intensity. When the rainfall intensity increases from 100 mm/h to 500 mm/h, the average water film thickness will increase by 3.26 times. The velocity of water film in the streamlined area of head car is larger than that in other areas, and the maximum velocity is 22.14 m/s. Compared with the rainless environment condition, the skin friction coefficient of the high-speed train increases and the average value will increase by 10.74% for a rainfall intensity of 500 mm/h. The positive pressure and resistance coefficient of the head car increase with the rainfall intensity. This research proposes a methodology to systematically analyze the generation of water film on the train surface and its influence on the train aerodynamic performance; the analysis can provide more practical results and can serve as a reference basis for the design and development of high-speed trains.

Cross-Granularity Infrared Image Segmentation Network for Nighttime Marine Observations

Infrared image segmentation in marine environments is crucial for enhancing nighttime observations and ensuring maritime safety. While recent advancements in deep learning have significantly improved segmentation accuracy, challenges remain due to nighttime marine scenes including low contrast and noise backgrounds. This paper introduces a cross-granularity infrared image segmentation network CGSegNet designed to address these challenges specifically for infrared images. The proposed method designs a hybrid feature framework with cross-granularity to enhance segmentation performance in complex water surface scenarios. To suppress feature semantic disparity against different feature granularity, we propose an adaptive multi-scale fusion module (AMF) that combines local granularity extraction with global context granularity. Additionally, incorporating a handcrafted histogram of oriented gradients (HOG) features, we designed a novel HOG feature fusion module to improve edge detection accuracy under low-contrast conditions. Comprehensive experiments conducted on the public infrared segmentation dataset demonstrate that our method outperforms state-of-the-art techniques, achieving superior segmentation results compared to professional infrared image segmentation methods. The results highlight the potential of our approach in facilitating accurate infrared image segmentation for nighttime marine observation, with implications for maritime safety and environmental monitoring.

Pollution Monitoring via Potentiometric Membrane Sensors for the Determination of Chlorpromazine Hydrochloride in the Presence of Its Main Photo-Degradation Products in River Water

The utilization of membrane sensors for the monitoring and determination of pharmaceutical environmental pollutants has emerged as a crucial objective in recent years. Given the extensive use of chlorpromazine hydrochloride (CPZ) in medicine, its presence in the environment, particularly in surface water such as rivers, is highly probable. Prolonged exposure of river water to sunlight and the photo-degradability of CPZ may enhance its photo-degradation. For the purpose of measuring CPZ in the presence of its primary photo-degradants, two sensitive and selective membrane electrodes were developed. These were synthesized utilizing two ion-pairing agents: sodium tetraphenylborate (TPB) and phosphotungstic acid (PTA). The electrodes exhibited a linear range that extended from 1 × 10−6 M to 1 × 10−2 M. The membrane electrodes of CPZ-TPB and CPZ-PTA exhibited slopes of 59.90 ± 0.60 mV/decade and 58.90 ± 0.80 mV/decade, respectively. The sensors mentioned above showed acceptable performance in a pH range of 2.0 to 6.0. All test parameters were optimized to provide superior electrochemical performance. The fabricated membranes were effectively employed to sensitively quantify CPZ in the presence of its principal photodegradants. The developed sensors were successfully employed to quantify CPZ in river water samples without necessitating pre-treatment procedures.

Long-term Coastline Monitoring in the Thanh Hoa Province (Vietnam) Using Landsat 5 and Landsat 8 Data

In recent years, extensive human activities have had a profound impact on the estuaries and coastal areas of Vietnam, most notably in coastal erosion and accretion. This paper used the Landsat multi-temporal data for the period 1988–2022 to assess coastline change in Thanh Hoa province (North Central Vietnam). Water indices calculated from Landsat imagery data, including NDWI, ANDWI, MNDWI, AWEInsh, AWEIsh, and BandWet, are used to extract surface water areas and then vectorize and overlay to estimate shoreline variability. The Otsu thresholding method is used to classify “water surface” and “land objects” and then evaluate the accuracy using the Kappa coefficient. The obtained results show that the ANDWI index has the highest accuracy in extracting the water body of the study area, in which the value of the Kappa coefficient reaches 0.95 compared to 0.91, 0.92, 0.93, 0.92 and 0.92 at using NDWI, MNDWI, AWEInsh, AWEIsh and BandWet indicies. Boundary vectorization and vector image overlays were performed to assess shoreline variability and map shoreline dynamics. The results obtained show that in the northern part of the coastal zone of Thanh Hoa province there is active accretion (increment) of the coastline. The average accretion rate was 150 m/year, the maximum rate was 457 m/year. In contrast, on the southern coast of Thanh Hoa province, coastline erosion predominates with a maximum rate of 38 m/year and an average rate of about 10 m/year.

Enhancing coloration performance and colour fastness of nano‐pigment ink‐jet‐printed blended fabrics through cationic and water‐repellent surface modification

AbstractThe coloration performance and colour fastness properties, crucial for industrial textile printing, depend on the spreading and fixation behaviour of ink‐jet droplets on porous fabrics. Current nano‐pigment‐based ink‐jet applications provide unstable results for these properties, especially for synthetic and blended fabrics. This study focuses on cellulose‐based blended fabrics as substrates to modify the wetting properties of fabrics through cationic and water‐repellent treatments, to improve the coloration performance and colour fastness systematically. The study conducted analytical experiments to analyse the surface element composition, ion potential and surface morphology of the fabrics. Differences in printing colour and pattern performance were attributed to the behaviour of ink droplet spreading on the fabric surface and inside the fabric, including wetting time, colourant distribution, and ring shape. The results indicate that ink droplet spreading on fabrics significantly influences printing pattern sharpness, including edge clarity and colour intensity, which can be improved through surface modification, including cationic and water repellent treatment. The use of blended fabrics treated with 1% cationic modifier and 0.05% fluorine‐containing water repellent resulted in effective suppression of droplet formation and significant enhancement of colour performance and fastness. Furthermore, as the ink droplet volume decreased from 5 to 1 μL, the coffee ring effect on the fabric treated with the water repellent agent gradually diminished, leading to improved printing sharpness during the printing process.

Characterization of Groundwater Geochemistry in an Esker Aquifer in Western Finland Based on Three Years of Monitoring Data

This study investigated the hydrogeochemistry of a shallow Quaternary sedimentary aquifer in an esker deposition in western Finland, where distinct spatial and temporal variability in groundwater hydrogeochemistry has been observed. Field investigation and hydrogeochemical data were obtained from autumn 2010 to autumn 2013. The data were analyzed using the multivariate statistical methods principal component analysis (PCA) and hierarchical cluster analysis (HCA), in conjunction with groundwater classification based on the main ionic composition. The stable isotope ratios of δ18O and δD were used to determine the origin of the groundwater and its connection to surface water bodies. The groundwater geochemistry is characterized by distinct redox zones caused by the influence of organic matter, pyrite oxidation, and preferential flow pathways due to different hydrogeological conditions. The groundwater is of the Ca-HCO3 type and locally of the Ca-HCO3-SO4 type, with low TDS, alkalinity, and pH, but elevated Fe and Mn concentrations, KMnO4 consumption, and, occasionally, Ni concentrations. The decomposition of organic matter adds CO2 to the groundwater, and in this study, the dissolution of CO2 was found to increase the pH and enhance the buffering capacity of the groundwater. The mobility of redox-sensitive elements and trace metals is controlled by pH and redox conditions, which are affected by the pumping rate, precipitation, and temperature. With the expected future increases in precipitation and temperature, the buffering capacity of the aquifer system will enhance the balance between alkalinity from bioactivity and acidity from recharge and pyrite oxidation.

Organic Farming in India: A Dual Strategy for Climate Change Adaptation and Mitigation

Recent decades have transformed Indian agriculture from traditional methods to a mechanized system reliant on fossil fuels, chemical fertilizers, and pesticides, increasing greenhouse gas emissions and impacting global climate. Higher greenhouse gas levels, including carbon dioxide, methane, and ozone are likely, causing the observed rise in air temperatures and leading to significant climate shifts. In most subtropical regions, a 4°C rise in global temperatures is anticipated to reduce groundwater and surface water, heightening food demand and threatening global food security. Climate change denotes long-term, significant alterations in climate measurements. A production system that maintains the health of ecosystems, soils, and human populations is known as organic farming (IFOAM 2006). Organic farming is energy-efficient and reduces greenhouse gas emissions by minimizing chemical and fossil fuel use, while enhancing soil carbon, biodiversity and fertility. It reuses plant and animal waste to restore soil nutrients, relies on renewable resources and supports sustainable, low-pollution management. Organic farming not only helps to mitigate climate change but also provides lasting benefits as an adaptation strategy. Effective nutrient management and carbon sequestration in soils are crucial for adapting and mitigating climate change across diverse temperature zones and local conditions.

Interfacial Assembly of Peptide Carbon Dot Hybrids Enables Photoinduced Electron Transfer with Improved Photoresponse.

Assemblies at the interface represent a powerful tool for integrating organic and inorganic components into hybrid nanostructures. Carbon dots are both excellent electron donors and acceptors, offering opportunities for their potential uses in light-harvesting applications. To further improve their functions, integration of acceptor carbon dots into donor organic nanostructures is of great interest for improving photophysical properties useful for photoinduced electron transfer. Here, a one-step protocol for the interfacial assembly of a two-component hybrid consisting of carbon dots and perylene containing an l-phenylalanine-based dipeptide through noncovalent bonding is developed. The perylene-containing dipeptide derivative formed micrometer-long nanofibers on the water surface through J-aggregate formation. Spectroscopic studies reveal photoluminescence quenching of the donor dipeptide upon increasing the concentration of acceptor carbon dots in the hybrid, suggesting photoinduced electron transfer from the donor peptides to acceptor carbon dots. The hybrids integrated in a planar device architecture show a significantly improved photoresponse because of the favorable interactions between the donor-acceptor components. The one-step integration of donor-acceptor hybrids on the water surface offers opportunities for light harvesting and related applications.

Divergence of nutrients, salt accumulation, bacterial community structure and diversity in soil after 8years of flood irrigation with surface water and groundwater.

Irrigation with saline groundwater has become necessary to overcome freshwater scarcity in the agricultural industry in arid areas. However, the effects of long-term saline groundwater irrigation on soil salinity and bacterial diversity have rarely been examined. In this study, a Lycium ruthenicum field was divided into two parts and subjected to flooding irrigation with saline groundwater (pH 7.81, total salinity 0.95g L-1) and surface water (pH 7.76, total salinity 0.36g L-1) for 8years. After 8years of irrigation, the soil salinity and salt ion content (i.e., Na+, Mg2+, K+, Ca2+, Cl- and CO32-) in the groundwater irrigation group were significantly greater than those in the surface water irrigation group (p < 0.001), with notable accumulation in the topsoil (0-5cm) (p < 0.01). The bacterial community structure differed between the surface water and groundwater irrigation groups. Salt-tolerant bacterial groups (e.g., Balneolaceae and Halomonadaceae) and species (e.g., the marine bacterium JK1007, the bacterium YC-LK-LKJ35, and Methylohalomonas lacus) dominated in the groundwater irrigation environment. Additionally, bacterial communities were associated primarily with soil salt ions (RV = 0.66, p < 0.001). The characteristic bacterial taxa in long-term groundwater irrigation soils were salt-tolerant species (e.g., the marine bacterium JK1007, the bacterium YC-LK-LKJ35, and Methylohalomonas lacus). These findings suggest that salinity is the key factor driving differences in bacterial community structure between long-term groundwater and surface water irrigation. The long-term use of surface water and groundwater for irrigation has different impacts on soil environments, with groundwater irrigation having a more pronounced negative effect. Highlights. The long-term effects of this practice on soil salt accumulation and bacterial diversity were examined. This study provides potential applications for sustainable land management in similar ecological contexts. Groundwater irrigation is characterized by saline-tolerant keystone species. Salinity filtering was used to determine the pattern of bacterial community construction.

Assessment of lake Markakol’s physical and chemical condition with consideration of eutrofication

The study was conducted in 2023 and comprised a comparative assessment of the state of Lake Markakol’s aquatic ecosystems in surface and bottom water strata. The analysis of bottom water temperatures showed correlation between this parameter and dissolved oxygen concentrations, indicating that pollution caused by organic impurities leads to lake eutrophication, in turn, pro-pelling the extinction of aquatic life. Although the main water physicochemical parameters of Markakol Lake correspond to the oligotrophic type, the shifts in dissolved oxygen and phos-phate content, as well as growth of aquatic vegetation indicate its transition to the mesotrophic type. Higher phosphate content in water is a consequence of pollution disturbing the biological balance, as well as stimulating the reservoir’s eutrophication and increased biological productivity, i.e. algal bloom. In addition, phosphate ions serve an informative indicator of Hazard Class 3 (organoleptically hazardous) anthropogenic pollution. Based on the correlation factor (r), two statistical models were considered for the target lake: 1) Water Pollution: nutri-ent concentrations depending on surface and bottom water temperatures (Model 1); and 2) changes in Water Pollution Indices (biogenic, heavy metals, mean) because of air temperature growth due to global warming of 0.25°C/decade (Model 2).

Determinant Factors of Microbial Drinking Water Quality at the Point of Use in Rural Ethiopia: A Case Study of the South Gondar Zone

Access to safe drinking water is a fundamental human need for health and well-being implemented globally by the United Nations under Sustainable Development Goal (SDG) 6. Storing drinking water is common in rural areas of Ethiopia due to off-premises water sources and intermittent piped water supply. However, this practice can lead to further contamination during collection, transport, and storage, posing a risk to public health. The objective of this study was to identify the determinant factors of drinking water quality at the point of use in the rural setting of northwestern Ethiopia, South Gondar zone. A questionnaire survey was conducted, and water samples from 720 households were collected during the wet and dry seasons. The determinant factors were identified using the multivariable logistic regression model. About 39.2% of the surveyed households had basic water supply services, 41.9% were using unimproved sources, and 8.3% were using surface water. Only 9.4% were using basic sanitation services, and 57.2% were practicing open defecation. Safe water storage was practiced by 84.3% of households, while only 2% engaged in household water treatment. About 14% of dry and 8% of wet season samples from the storage were free from fecal coliform bacteria. Furthermore, 52.9% of dry and 62.2% of wet season samples fell under the high microbial health risk category. The season of the year, the water source type, storage washing methods, and the socioeconomic status of the household were identified as key predictors of household drinking water fecal contamination using the multivariable logistic regression model. It was observed that the drinking water in households had a high load of fecal contamination, posing health risks to consumers. To tackle these problems, our study recommends that stakeholders should enhance access to improved water sources, implement source-level water treatment, increase access to improved sanitation facilities, advocate for safe household water management practices, and endorse household water treatment methods.

Groundwater potential mapping in semi-arid region of Northern Nigeria by integrating analytic hierarchy process and GIS

Groundwater resource management in drylands, characterized by climate variability and population growth, is difficult. Exploration and exploitation of groundwater, due to inadequate surface water is very costly. This study employed the analytic hierarchy process (AHP) and GIS to identify groundwater potential (GWP) areas in a semi-arid region of Nigeria. Land-use-land-cover, drainage density, slope, rainfall, static water level, soil, lithology, and aquifer were selected for GWP analysis. Parameter weights were determined using AHP and ranked based on their contribution to GWP by experts. The parameters were then integrated using the weighted overlay tool in ArcGIS 10.5 to produce a GWP map of the study area. Borehole yield data from 245 wells were collected to determine the model accuracy and model validation. Results classified the study area into very high GWP (1.9%), high GWP (8.8%), moderate GWP (62%), low GWP (20.70%) and very low GWP (6.6%). Areas with better GWP include Gurun, Dugol, Zago, Kumbo, Dukku, Doguwa, Riruwai, Dambazau, etc. Moderate GWP areas are widely spread across the state while areas with poor GWP include Sharawa, Kadewa, Koya, Dagar, Jigilawa, Galwanga, Yanganau, Kunchi, Tofa, Tsanyawa, etc. Validation of the AHP model with borehole yield data shows a correlation coefficient of 71.3% giving a good prediction. AHP and GIS can be used to successfully map GWP areas which could serve as an exploration guide for sustainable management of groundwater resources in semi-arid areas.

Urban transformation of lakes and its impacts on a lake series: A case study of the yele mallappa shetty lake series Bengaluru, India.

The interconnected systems of lakes of Bengaluru, India, experience tremendous stress due to unsustainable urbanisation. Traditional lake-centric research approach struggles to capture and address this issue due to the cascaded nature of impacts in interconnected lake systems. Hence, this study assesses the impact of urbanisation on a lake series scale, focusing on the Yele Mallappa Shetty Lake series (YMSLS). Land use land cover change analysis (1993-2023) showed that in 1993, the YMSLS catchment area was dominated by open spaces (53.4%) and agriculture land and vegetation (35%), with built-up areas covering only 7.2%. By 2023, the built-up area has expanded to 34.6% and became the dominant land use. This rapid urbanisation has led to increased water surface area from wastewater influx, causing significant weed growth and water pollution in the lakes. Lake water quality assessment showed that faecal coliform, total coliform, dissolved oxygen, and biochemical oxygen demand levels exceeded standard limits with spatio-temporal variations driven by interconnectivity. Pollutant flushing during monsoon reduced pollution load in upstream lakes, but high wastewater inflow made downstream lakes, particularly the end lake, highly polluted but perennial. Increased water availability expanded the user base of the end lake, but traditional uses have declined and coping strategies of users, such as wastewater lift irrigation from the lake, became unsustainable. The study indicates that spatial interdependence and cascading effects necessitate a lake series approach for assessing the impacts of urbanisation on interconnected lake system, which is crucial for enhancing water security and preparedness for future extreme events.

Micro- and mesoplastic pollution in the surface water and nekton from the Eastern Indian Ocean: Spatiotemporal variation, correlation and risk assessment.

The pollution of micro- and mesoplastic (MMP) in the Eastern Indian Ocean (EIO) remains poorly understood. The present study revealed that MMP abundance in nekton from EIO in 2022 (mean: 2.30 ± 0.39 items individual-1 and 1.81 ± 0.54 items g-1) was significantly higher than that in 2021 (mean: 1.60 ± 0.22 items individual-1 and 0.80 ± 0.13 items g-1). In contrast, MMP abundance in surface water varied insignificantly between 2021 (mean: 0.04 ± 0.01 items m-3) and 2022 (mean: 0.05 ± 0.02 items m-3). The rise in predominant polymers-polypropylene (PP), rayon (RA), and polyester (PES)-in nekton from 2021 to 2022 may suggest increased pollution from face masks and home textiles along coastal regions. Notable spatial variation in PP and RA between the northeastern and southeastern regions was observed only in nekton, suggesting they are better indicators of MMP spatiotemporal variation than surface water. Shadow driftfish ingested more MMPs than purpleback flying squid and mackerel scad, likely due to its deeper habitat. By simultaneously considering color, composition, and shape, integrated MMP analysis showed insignificant correlation between MMP pollution in surface water and nekton, suggesting that nekton may ingest MMPs through multiple pathways beyond surface water. Risk indices for surface water and nekton reached moderate to upper levels globally, emphasizing the need for continued monitoring in the EIO. Epoxy resin, rubber, and PP + acrylic were identified as the most hazardous polymers, providing a valuable basis for developing effective strategies to mitigate plastic pollution.

Underwater-to-air distorted image correction based on the reconstructed water surface

Abstract The lights with spatial target information received by the underwater camera are refracted at the intersection with the water surface, resulting in geometric distortion of the image. Existing methods for correcting the water-to-air distorted images typically rely on a large amount of data, such as image sequences, making the restoration using a single frame challenging. To address the issue, we propose a spatial pixel correction algorithm based on the reconstructed water surface. Firstly, we introduce a gradient water surface reconstruction algorithm based on the discrete normal vector, ensuring high accuracy in the spatial position and amplitude of the reconstructed water surface. Thus, intersections of the lights with the reconstructed water surface can be solved based on the constructed water surface. Subsequently, we propose a camera’s reverse tracking algorithm, which skillfully links the images with the spatial pixel coordinates. Finally, based on the characteristics of pixel arrangement, we propose a spatial grid algorithm to separate the spatial coordinates obtained by the reverse tracking algorithm. This part can better handle the highly concentrated and over-dispersed pixels in the spatial coordinate system. The proposed correction algorithm has better correction performance. The similarity between the restored and real images is more than 80%, and the mean square error is less than 0.01.

Response of dissolved organic matter and disinfection by-product precursors to algal blooms and thermal stratification in deep reservoirs.

Algal bloom contribute substantially to dissolved organic matter (DOM) and disinfection by-product (DBP) precursors in deep reservoirs, threatening drinking water safety. However, the variations in DOM and DBP precursors in deep-water reservoirs during algal bloom remain unclear. UV and fluorescence spectroscopy and chlorination experiments were used to analyze the variations in DOM and DBP precursors during algal bloom in the Sanhekou Reservoir. Before algal bloom, the DOM and DBP precursors decreased due to biodegradation. After algal bloom, the DOM and DBP precursors increased by 48.3% and 86.9% due to algae producing protein-like compounds. Notably, the algal bloom produced a range of nitrogenous compounds that significantly promote the formation of trichloronitromethane, a major contributor to the mammalian cytotoxicity associated with DBPs. In addition, the heterogeneous matrix led to the stratification of DOM and DBP precursors. The surface water (0-5 m) was more vulnerable to algae, with protein-like components being much higher than in other layers, while humic and fulvic-like components were much lower. However, high temperatures and sufficient oxygen conditions accelerated the biodegradation of DOM and DBP precursors, resulting in significantly lower levels of DOM and DBP precursors in the surface water compared to other layers (p<0.05). This study provides insights into the variations and the drivers in DOM and DBP precursors during algal bloom, essential for developing water intake strategies in similar water reservoirs.

Trace Element Composition of Surface Water in Almaty City and Human Health Risk Assessment

This investigation meticulously examined the elemental composition of 64 water samples collected during the seasons of spring, summer, autumn, and winter of the year 2023. The average seasonal concentrations of arsenic (As), beryllium (Be), cobalt (Co), cadmium (Cd), copper (Cu), lithium (Li), molybdenum (Mo), nickel (Ni), lead (Pb), selenium (Se), uranium (U), mercury (Hg), aluminum (Al), barium (Ba), chromium (Cr), iron (Fe), manganese (Mn), strontium (Sr), vanadium (V), zinc (Zn), calcium (Ca), potassium (K), magnesium (Mg), sodium (Na), and chlorine (Cl) as well as SO4 and dry residue were computed at 16 strategically selected sites along the Bolshaya and Malaya Almatinka, Esentai, and Kargalinka rivers situated in Almaty. The sampling locations were categorized into three distinct sectors: upper (adjacent to mountainous regions), middle (urban zone), and lower (exceeding city limits), thereby facilitating the examination of discrepancies in water quality and elemental concentrations. The results reveal that surface water resources in Almaty, particularly concerning As, Ni, Cr, U, and Pb, may present a considerable carcinogenic risk if utilized for consumption purposes. This is especially alarming given that these rivers constitute a vital source of drinking water for the inhabitants of the city. Specifically, at two sampling locations along the Bolshaya and Malaya Almatinka rivers in proximity to significant urban thoroughfares, untreated river water displayed an elevated carcinogenic risk (CR ~ 10−2). These results highlight the urgent necessity for enhanced water treatment and ongoing monitoring to safeguard public health.

Delineation of Groundwater Potential Using the Bivariate Statistical Models and Hybridized Multi-Criteria Decision-Making Models

Identifying groundwater potential zones in a basin and developing a sustainable management plan is becoming more important, especially where surface water is scarce. The main aim of the study is to prepare the groundwater potential maps (GWPMs) considering the bivariate statistical models of frequency ratio (FR), weight of evidence (WoE), and the multi-criteria decision-making (MCDM) model of Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) hybridized with FR and WoE. Two distance measures, Euclidean and Manhattan, were used in TOPSIS to evaluate their effect on GWPMs. The research focused on the Burdur Lake catchment located in the southwest of Türkiye. In total, 74 wells with high yields were chosen randomly for the analysis, 52 (70%) for training, and 22 (30%) for testing processes. Sixteen groundwater conditioning factors were selected. The area under the receiver operating characteristic (AUROC) and true skill statistics (TSS) were utilized to examine the goodness-of-fit and prediction accuracy of approaches. The TOPSIS-WoE-Manhattan model and the FR and WoE models gave the best AUROC values of 0.915 and 0.944 for the training and testing processes, respectively. The best TSS values of 0.827 and 0.864 were obtained by the TOPSIS-FR-Euclidean and WoE models for the training and testing processes, respectively.

Characteristics of deep-sea microbial cellulases: key determinants of the ultimate fate of plant biomass on Earth

AbstractLand plants, especially those with significant woody biomass, represent the largest source of biomass on Earth, making the biodegradation of lignocellulosic materials critical to understanding the global carbon cycle. Cellulose, a major component of lignocellulose, is notoriously resistant to degradation due to its highly crystalline structure. While the degradation of cellulose by terrestrial microbes has been extensively studied, the mechanisms of cellulose degradation in deep-sea environments remain largely unexplored. The deep-sea ecosystem depends on organic matter, such as cellulose, that is synthesized in terrestrial environments and surface waters and descends to the deep sea. Recent studies suggest that a significant amount of cellulose is likely to reach the deep sea. Here, we present an in-depth study of cellulases from a novel deep-sea γ-proteobacterial strain TOYAMA8, isolated from Toyama Bay, Japan, using Surface Pitting Observation Technology (SPOT), a highly sensitive assay for enzymatic cellulose hydrolysis. The cellulases of strain TOYAMA8 show similarities to those of a previously reported deep-sea cellulolytic microbe, Marinagarivorans cellulosilyticus strain GE09. Genomic and transcriptomic analyses of these strains reveal novel cellulase genes and mechanisms that differ from terrestrial counterparts, shedding light on the unique adaptations of deep-sea microbes to recalcitrant biomass. In particular, these strains produce high-molecular-weight cellulases with unique domain architectures, likely optimized for membrane anchoring, which prevents enzyme diffusion and ensures efficient localized activity. Our findings provide critical insights into the microbial cellulose degradation in the deep sea, highlighting its role in the fate of organic carbon and the potential for biotechnological applications in biorefineries.

Light‐Manipulated Millimeter‐Scale Swimming Robot for Precise Navigation

AbstractMicro‐swimming robots have been increasingly emphasized in the fields of targeted drug delivery and water surface cleaning, which mainly use open external structures or external environments to assist navigation, but there are still salient problems, such as the difficulty of stable capture and poor navigation accuracy. Theoretically, a light‐driven swimming robot can have a symmetrical embedded structure to constrain surface tension gradient forces and thermophoretic forces in a wide range of directions and convert them into precise directional forces. Therefore, a sustained‐capture swimming robot is developed with precise navigation consisting of TiO2/polypyrrole (PPy) composites containing a symmetric inner truncated‐cone hole structure and realized multiple controllable motion patterns. Excitingly, the capture motion of the TiO2/PPy inner truncated‐cone hole structure robot “TPHR” can be accurately controlled by programmable automation, with capture travel speeds of up to ≈23.64 mm s−1. Its excellent kinematic performance stems from the high photothermal conversion efficiency (≈47.83%) of the composite and the synergistic effect between thermo‐capillary and thermo‐convective flows. Furthermore, a patterning precision movement, water surface oil‐cleaning microstructure assembly, etc. are realized, reflecting the engineering application value of TPHR. This structure provides a novel strategy for the development of micro‐swimming robots with stable capture and sustainable motion.