The construction time of concrete structures in hydraulic tunnels is long, the construction environment is complex, and there are many influencing factors. The requirements for construction quality are high, not only to meet the strength requirements, but also to meet the design requirements of erosion resistance, crack resistance, and seepage resistance according to its specific operating environment. Therefore, evaluating the construction quality of concrete structures in hydraulic tunnels is of great significance. Considering the randomness and fuzziness of factors affecting the construction quality of concrete structures in hydraulic tunnels, this paper proposes a comprehensive evaluation model based on Combined Weighting (CWM) and Uncertainty Measurement Theory (UM). The IAHP method and CRITIC method are used to determine the subjective and objective weights of evaluation indicators, combined weighting is based on the principle of minimum entropy, and the UM method is used to evaluate the construction quality level. Finally, taking a hydraulic tunnel as an example, its construction quality grade is calculated to be III according to the evaluation model proposed in this paper, which matches with the engineering reality, and a comparative study is made with the mixture element topology theory at the same time. It is verified that the evaluation model can scientifically and reasonably evaluate the construction quality level of concrete structures in hydraulic tunnels.

We prove an analog of the removable singularity theorem for bounded harmonic functions on stratified sets. The harmonic functions are understood in the sense of the soft Laplacian. The result can become one of the main technical components for extending the well-known Poincaré–Perron’s method of proving the solvability of the Dirichlet problem for the soft Laplacian.

This study extends the CGAN-based MODIS cloud vertical-profile (64×64-scene, about 70km width×15km height) retrieval technique developed by Leinonen et al. (2019) [1] to construct seamless 3D cloud fields for the MODIS granules [2]. Firstly, the accuracy and spatial continuity of the Leinonen et al. [1] retrievals are statistically evaluated. Then, according to the characteristics of the retrieval error, a spatially overlapping-scene ensemble generation method and a bi-directional Ensemble Binning Probability Fusion (CGAN-BEBPF) technique are developed, which improves the CGAN retrieval accuracy and support to construct seamless 3D clouds. The CGAN-BEBPF technique involves three steps: cloud masking, intensity scaling, and optimal value selection. It ensures adequate coverage of the low reflectivity areas while preserving the high reflectivity cloud cores. The technique is applied to retrieve the 3D cloud fields of Typhoon Chaba and a multi-cell convective system. The cloud structures of the CGAN-BEBPF results are highly consistent with the ground-based radar observations. It can retrieve weak clouds at the top levels of convective storms and hurricanes that were missed by ground-based radars and fill the gaps of the ground-based radar lower-level PPI scan. Overall, CGAN-BEBPF can be automated to retrieve the rich informative 3D structures of typhoons and severe convective systems over the oceans along the MODIS swath, which certainly presents great value for improving maritime and near-shore typhoons and convection prediction and other cloud-sensitive applications.

Effective water resources management requires assessments of water availability within a framework of complex institutions and infrastructure employed to manage extremely variable stream flow shared by numerous often competing water users and diverse types of use. The Water Rights Analysis Package (WRAP) modeling system is fundamental to water allocation and planning in the state of Texas in the United States. Integration of environmental flow standards into both the modeling system and comprehensive statewide water management is a high priority for continuing research and development. The public domain WRAP software and documentation are generalized for application any place in the world. Lessons learned in developing and implementing the modeling system in Texas are relevant worldwide. The modeling system combines: (1) detailed simulation of water right systems, interstate compacts, international treaties, federal/state/local agreements, and operations of storage and conveyance facilities; (2) simulation of river system hydrology; and (3) statistical frequency and reliability analyses. The continually evolving modeling system has been implemented in Texas by a water management community that includes the state legislature, planning and regulatory agencies, river authorities, water districts, cities, industries, engineering consulting firms, and university researchers. The shared modeling system contributes significantly to integration of water allocation, planning, system operations, and research.

The Upper Hunter Valley is a major coal mining area in New South Wales (NSW), Australia. Due to the ongoing increase of mining activities, PM10 (air-borne particle with an aerodynamic diameter less than 10 micrometres) pollution has become a major air quality concern in local communities. The early part of this study identified two air quality subregions in the valley. This paper aims to provide a holistic summarisation of the relationships between elevated PM10 pollution in two subregions and the local- and synoptic-scale meteorological conditions for spring and summer, when PM10 pollution is relatively high. A catalogue of twelve synoptic types and a set of six local meteorological patterns have been quantitatively derived and linked to each other using the self-organising map (SOM) technique. The complex meteorology-air pollution relationships have been visualised/interpretated on the SOM planes for two representative locations. It was found that the influence of local meteorological patterns differed significantly for mean PM10 levels vs the occurrence of elevated pollution events and between air quality subregions. In contrast, synoptic types showed generally similar relationships with mean vs elevated PM10 pollution in the valley. Two local meteorological patterns, the hot-dry-northwesterly wind conditions and the hot-dry-calm conditions, were found most PM10 pollution conducive in the valley when combined with a set of synoptic counterparts. These synoptic types are featured with the influence of eastward migrating continental high pressure system and westerly troughs, or a ridge extending northwest towards coastal northern NSW or southern Queensland from the Tasman Sea. The method and results can be used in air quality research for other locations of NSW, or similar regions elsewhere.

Rubella infection is typically mild or asymptomatic except when infection occurs during pregnancy. Infection in early pregnancy can cause miscarriage, stillbirth, or congenital rubella syndrome. Only individuals that are still susceptible to rubella infection during child-bearing age are vulnerable to this burden. Rubella containing vaccine (RCV) is safe and effective, providing life-long immunity. However, average age-at-infection increases with increasing vaccination coverage, which could potentially lead to increased disease burden as well, if the absolute risk of infection during child-bearing age increases. Dynamics of rubella transmission were explored using EMOD, a software tool for building stochastic, agent-based infection models. Simulations of pre-vaccine, endemic transmission of rubella virus introduced RCV at varying levels of coverage to determine the expected future trajectories of disease burden. Introducing RCV reduces both rubella virus transmission and disease burden for a period of around 15 years. Increased disease burden is only possible more than a decade post-introduction, and only for contexts with low current burden and high transmission intensity. Low or declining rubella virus transmission intensity is concurrently associated with both greater disease burden and greater vaccine effectiveness. The risk of increasing burden through vaccination only exists for locations with persistently high infectivity, high connectivity, and high fertility. A trade-off between the risk of a small, future burden increase and a large, immediate burden decrease strongly favors RCV introduction.

China’s greenhouse industry has thousands of years of development history, although the development of modern greenhouses has come late. After decades of development of China, its greenhouse industry is in the forefront of the world. China’s greenhouse industry is experiencing rapid development, transformation and upgrading. China ranks first in the world in terms of greenhouse area, used mainly for vegetable cultivation and plays an important role in the utilization of agricultural resources and food production. In 2023, the cumulative area of new greenhouses nationwide was 1835.87 million ha. In this paper we present the latest developments in the greenhouse sector. More specifically, we present a greenhouse market development overview, the greenhouse production, the greenhouse industry, and technology development. Current problems are underpinned, development opportunities and prospects are analyzed, and measures and specific proposals are detailed for the technological development of the greenhouse sector both for increasing product quantity and quality.

: Tunnel instability and lining integrity are intimately tied to the creep properties of the surrounding rock. The acquisition of rock mass creep parameters is critical in ascertaining the appropriate timing for lining construction. Nevertheless, creep tests on rock specimens conducted in a controlled setting cannot be straightforwardly extrapolated to rock mass creep analysis. This study performs laboratory-based creep tests on mudstone samples and establishes the corresponding creep constitutive model. Integration of a Mohr-Coulomb element with the Burgers model in series serves to characterise the yield creep behaviour of the rock mass. Additionally, the research outlines a series of 100 orthogonal experiments utilising randomised creep parameters, and formulates a GA-BP neural network inversion model. Employing long-term deformation measurements from the crown and sidewalls of the project site, this study deduces the creep parameters of the mudstone in the investigated tunnel section and examines the prolonged deformation traits of the surrounding rock. Drawing on the deformation traits of the surrounding rock and the forces impacting the primary support and lining structures, this paper evaluates the earliest and latest viable lining casting periods and pinpoints an optimal timing interval for lining implementation. The methodologies employed herein can serve as a benchmark for analogous endeavors internationally.

In the process of sewage coagulation treatment, quartz sand is often used as a heavy medium to accelerate the settling rate of flocs, but it will adversely affect the removal efficiency of pollutants. The factors that affect the coagulation effect and can be controlled manually include the quartz sand dosage, coagulant dosage, sewage pH, stirring time, settling time, etc, their reasonable setting is critical to. This paper was to study the optimal conditions of quartz sand enhanced coagulation(QSEC), first, single-factor tests were conducted to preliminarily explore the optimal range of influencing factors, and then response surface methodology（RSM）tests were performed to accurately determine the optimums of significant factors. The results showed that the addition of quartz sand can’t improve the water quality of coagulation treatment, but it can significantly accelerate the coagulation settlement process, the quartz sand dosage, the coagulant dosage and sewage pH all impacted significantly on its coagulation effect, and existed inflection points. A model that could guide QSEC was obtained by RSM tests. The model optimization and experimental validation showed that the optimal QSEC conditions for treating domestic sewage were as follows: the polyaluminum chloride(PAC) dosage, cationic polyacrylamide(CPAM) dosage, the sewage pH, quartz sand dosage, stirring time and settling time were 0.97 g·L-1, 2.25 mg·L-1, 7.22, 2 g·L-1, 5 minutes and 30 minutes, respectively, and the turbidity of treated sewage was reduced to 1.15 NTU.

Climate change is a global issue that draws widespread attention from the international society. As an important component of the climate system, the water cycle is directly affected by climate change. Thus, it is very important to study the influences of climate change on the basin water cycle with respect to maintenance of healthy rivers, sustainable use of water resources, and sustainable socioeconomic development in the basin. In this study, by assessing the suitability of multiple General Circulation Models (GCMs) recommended by the Intergovernmental Panel on Climate Change, Statistical Downscaling Model (SDSM) and Automated Statistical Downscaling model (ASD) were used to generate future climate change scenarios. These were then used to drive distributed hydrologic models (Variable Infiltration Capacity, Soil and Water Assessment Tool) for hydrological simulation of the Yangtze River and Yellow River basins, thereby quantifying the effects of climate change on the basin water cycle. The results showed that suitability assessment adopted in this study could effectively reduce the uncertainty of GCMs, and that statistical downscaling was able to greatly improve precipitation and temperature outputs in global climate mode. Compared to a baseline period (1961–1990), projected future periods (2046–2065 and 2081–2100) had a slightly decreasing tendency of runoff in the lower reaches of the Yangtze River basin. In particular, a significant increase in runoff was observed during flood seasons in the southeast part. However, runoff of the upper Yellow River basin decreased continuously. The results provide a reference for studying climate change in major river basins of China.

Plain lakes play a crucial role in the hydrological cycle of a watershed, but their interactions with adjacent rivers and downstream water bodies can create complex river-lake relationships, often leading to frequent flooding disasters. Taking Poyang Lake as an example, this paper delves into its interaction with the Yangtze River, revealing the spatiotemporal patterns of flood propagation within the lake and its impact on surrounding flood control measures. The aim is to provide insights for flood management in similar environments worldwide. This study employs a comprehensive approach combining hydrological statistical analysis and two-dimensional hydrodynamic modeling, based on extensive hydrological, topographic, and socio-economic data. The results indicate that the annual maximum outflow from Poyang Lake is primarily controlled by floods within the watershed, while the highest annual lake water level is predominantly influenced by floods from the Yangtze River. The peak discharge typically reaches the lake outlet within 48 hours, with the peak water level taking slightly longer at 54 hours. However, water storage in the lake can shorten the time for the peak discharge to arrive. When converging with floods from the Yangtze River, the peak water level may be delayed by up to 10 days due to the top-supporting interaction. Furthermore, floods from the "Five Rivers" propagate differently within the lake, affecting various lake regions to differing degrees. Notably, floods from the Fu River cause the most significant rise in lake water level under the same flow rate. The top-supporting effect from the Yangtze River also significantly impacts the water surface slope of Poyang Lake. When the Yangtze River flood discharge far exceeds that of the "Five Rivers" (i.e., when the top-supporting intensity f value exceeds 4), the lake surface becomes as flat as a reservoir. During major floods in the watershed, the water level difference in the lake can increase dramatically, potentially creating a "dynamic storage capacity" of up to 840 million cubic meters.

The majority of existing numerical simulations of the effect of bridge piers on water movement are based on a limited number of bridge piers at a laboratory scale. Furthermore, some 2D numerical simulations for actual bridge projects have deficiencies, including the use of overly large mesh sizes and an inadequate treatment of bridge piers. In this study, we compare three methods of structural mesh encryption, suspension mesh, and nonstructural mesh based on Delft3D, and apply the optimization scheme to a real bridge project. It is demonstrated that optimal results can be achieved by utilising a grid size comparable to the pier diameter (Dp) in the region away from the piers. In the vicinity of the piers, the grid cell size should be no larger than 1/9 Dp. The suspended grid technique (DD Boundary) can yield results consistent with those obtained using a full-area high-resolution grid, provided that the total number of grids can be reduced and the computational time is considerably reduced. In this study, the unstructured mesh (Deflt3D Flexible Mesh) scheme was unable to capture the oscillations of the wake flow behind the bridge piers. However, the application of the optimized scheme in bridge engineering has demonstrated its practical value. The findings of this study on mesh resolution and suspension mesh scheme can be applied to the Delft3D software and are also useful for other numerical simulation work.

Very heavy stratiform precipitation (> 200 mm/per day) occurred in the Hokitika region on the west coast of the South Island of New Zealand on 18 June 2015, under north-westerlies with small CAPE (< 25 J/kg). Analyses of model simulations and observations showed that this heavy rainfall was due to cold front lifting enhanced by orographic lifting over the Southern Alps. At 1.5 km grid-length, the model terrain underestimated the average height of the 103 tallest mountains over the South Island by ~ 800 m. This leads to weaker orographic lifting and mountain blocking, and a faster-moving and stronger cold front in the Hokitika region. As a result, large errors in the heavy rainfall prediction occur. By increasing either the resolved or the sub-grid mountain heights, the simulated rainfall errors were largely reduced through stronger orographic lifting and mountain blocking, and a better simulation of the cold front movement and strength. All the experiments have the same “flow-over” regime with mountain waves and/or wave breaking (Fm ranges 0.61 – 1.21). However, the rainfall amount and distribution on the windward side of mountains altered significantly. Our new findings were that the Southern Alps can have significant indirect effects on heavy rainfall by altering the speed and strength of the cold front, in addition to the well-known direct dynamical effects (i.e., orographic lifting and mountain blocking). A combination of these direct and indirect effects makes the heavy rainfall simulation sensitive to mountain heights even under the same “flow-over” regime.

The European Union Water Framework Directive (2000/60/EC; WFD) aims to achieve a good ecological and chemical status of all bodies of surface water by 2027. The development of an integrated guidance on surface water chemical monitoring (e.g. WFD Guidance Document No. 7/19) has been transferred into national German law (Ordinance for the Protection of Surface Waters, OGewV). For the majority of compounds, this act requires a monthly sampling frequency to assess the chemical water quality status of a surface water body. To evaluate the representativeness of the sampling strategy under the OGewV, high-frequency online monitoring data is investigated under different sampling scenarios and compared with current, monthly grab sampling strategy. About 23 million data points were analyzed for this study, three chemical parameters (dissolved oxygen, nitrate-nitrogen, chloride concentration) and discharge data were selected from four catchment of different sizes ranging from 51391 km² to 84 km² (Elbe, Vereinigte Mulde, Neiße and two stations at Lockwitzbach). In this paper we proposed short-term online-monitoring (STOM) as a sampling alternative. STOM considers the placement of online sensors over a limited duration and return interval. In general we: (I) compare the results of conventional grab sampling with STOM, (II) investigate the different performance of STOM and grab sampling using discharge data as proxy for analyzing event-mobilized pollutants and (III) investigate the related uncertainties and costs of both sampling methods. Results show, that STOM outperforms grab sampling for parameters where minimum/maximum concentrations are required by law as the probability to catch a single extreme value is higher with STOM. Furthermore, parameters showing a pronounced diurnal pattern, like dissolved oxygen, are also captured considerably better. The performance of STOM showed no substantial improvements for parameters with small concentration variability, as nitrogen-nitrate The analysis of discharge events as a proxy parameter for event-mobilized pollutants proved that the probability of capturing samples during events is significantly increased by STOM.

We construct a Bayesian estimator for the dilution of a wastewater sample. When wastewater is diluted by rainwater an estimate of the level of dilution is required if we are to normalise sample measurements of disease markers such as SARS-CoV-2 RNA. We consider the situation where flow measurements are available, but will regularly be unreliable because of the action of combined sewer outflows (CSOs) and wastewater storage tanks, which divert wastewater away from treatment plants when the flow is excessive. However, we also have proxies for the flow from various chemical markers (e.g.\ phosphate, ammonium, electrical conductivity), whose level per unit of population is fixed. The new flow estimator has multiple advantages compared to existing procedures: credible intervals for the estimates; optimal weighting of the chemical markers; systematic handling of missing and censored values; and model based smoothing without lags.

Innovations and improvements in hydraulic fracturing and horizontal well technologies have contributed to the success of the shale gas industry; however, the industry is also challenged by freshwater use and environmental health issues. Increasing water impact makes precise quantification of water consumption important. The objective in this study was to better understand water sustainability and availability of the projected shale gas from 2018 to 2030 in the Weiyuan play, China. The water footprint framework was used to quantify the potential water use and environmental impacts on different time scales. The results showed that the water use per well ranged from 11351.3 to 60664.73 m3, with a median of 36013.94 m3, totaling ~3.44 Mm3 for 97 wells. Yearly evaluation results showed that the gray water footprint was the main contributor and accounted for 83.82% to 96.76%, which was dependent on different scenarios of treatment percentages. The monthly environmental impact results indicated that the annual streamflow statistics were more likely to prevent water withdrawal. Water quality issues may be alleviated through recycling and retreatment measures that improve current waste water management strategies. Resource regulators should manage their water resources by matching water demand to water availability or replenishment.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social interaction and communication, anxiety, hyperactivity, and restricted interest for specific subjects. In addition to the genetic factors, multiple environmental factors have been related to the development of ASD. Animal models can serve as crucial tools for understanding the complexity of ASD and identifying potential therapeutic strategies. In this study, a chemical model of ASD has been developed in zebrafish by exposing embryos to valproic acid (VPA) from 4 to 48 hours post-fertilization. After the exposure, embryos were transferred to fish water and the effects on behavior and neurotransmitters profile were analyzed at both larval and adult stages. Larvae from VPA-treated embryos showed hyperactivity and decreased visual and vibrational escape responses, as well as an altered neurotransmitters profile, with increased glutamate and decreased acetylcholine and norepinephrine levels. Adults from VPA-treated embryos exhibited impaired social behavior characterized by larger shoal sizes and a decreased interest for their conspecifics. Neurotransmitter analysis revealed a significant decrease in dopamine and GABA levels in the brain. These results support the interest of this model in the study of ASD.

This study utilises NaOH to treat composite cementitious materials containing aeolian sand and zeolite powders, which were used to replace 50% of the cement in aeolian-sand concrete (ASC). The mechanical properties of treated ASC considerably improved, especially when the NaOH dosage was 4% by mass. After curing this sample (denoted as AAZC-4) for 28 d, its compressive strength improved by 17.2% and its split tensile was increased by 16.3%. Potassium feldspar and montmorillonite in zeolite powder and SiO2 in the sand were decomposed by OH− and combined with other elements to generate various silicate gels and A-type potassium zeolite crystals inside the concrete. Microscopic examination showed that the gels and crystals intertwined to fill the pores, decreasing (increasing) the percentage of large (small) pores, thus optimising the pore structure. This substantially improved the mechanical properties of ASC. Freeze–thaw salt-intrusion tests showed that the extent of mass loss, degree of damage and loss of compressive strength of AAZC-4 were similar to those of ordinary concrete but were reduced by 36.8%, 19% and 52.1%, respectively, compared with those of ASC. Therefore, AAZC-4 has sustainable working performance in the chloride ion permeable environment in cold and arid areas.

Droughts have a substantial effect on water resources, agriculture, and ecosystems on a worldwide scale. In the Mekong Delta of Vietnam, droughts exacerbated by climate change are significantly endangering the region's agricultural sustainability and output. Conventional forecasting techniques frequently do not capture the intricate dynamics of meteorological phenomena associated to drought effectively, prompting the exploration of more advanced methodologies. This work utilises artificial intelligence, par-ticularly machine learning methods like Gradient Boosting and Extreme Gradient Boosting (XGBoost), to enhance drought pre-diction in the Mekong Delta. The study utilises data from 11 meteorological stations spanning from 1990 to 2022 to create and evaluate Machine Learning models based on several climatic factors. We utilise Gradient Boosting and XGBoost algorithms to estimate the Standardised Precipitation-Evapotranspiration Index (SPEI) and evaluate their effectiveness in comparison to con-ventional forecasting techniques. The results show that Machine Learning, particularly XGBoost, surpasses traditional approaches in predicting SPEI accuracy at various time scales. XGBoost demonstrates skill in understanding the complex relationships between climatic factors, with R² values falling between 0.90 and 0.94 for 1-month forecasts. The progress highlights the potential of Machine Learning in improving drought management and adaptation tactics, proposing the incorporation of Machine Learning forecasting models into decision-making processes to enhance drought resistance in susceptible areas.

Large-scale hydrological modeling in China is challenging given the sparse meteorological stations and large uncertainties associated with atmospheric forcing data.Here we introduce the development and use of the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) in the Heihe River Basin(HRB) for improving hydrologic modeling, by leveraging the datasets from the China Meteorological Administration Land Data Assimilation System (CLDAS)(including climate data from nearly 40000 area encryption stations, 2700 national automatic weather stations, FengYun (FY) 2 satellite and radar stations). CMADS uses the Space Time Multiscale Analysis System (STMAS) to fuse data based on ECWMF ambient field and ensure data accuracy. In addition, compared with CLDAS, CMADS includes relative humidity and climate data of varied resolutions to drive hydrological models such as the Soil and Water Assessment Tool (SWAT) model. Here, we compared climate data from CMADS, Climate Forecast System Reanalysis (CFSR) and traditional weather station (TWS) climate forcing data and evaluatedtheir applicability for driving large scale hydrologic modeling with SWAT. In general, CMADS has higher accuracy than CFRS when evaluated against observations at TWS; CMADS also provides spatially continuous climate field to drive distributed hydrologic models, which is an important advantage over TWS climate data, particular in regions with sparse weather stations. Therefore, SWAT model simulations driven with CMADS and TWS achieved similar performances in terms of monthly and daily stream flow simulations, and both of them outperformed CFRS. For example, for the three hydrological stations (Ying Luoxia, Qilian Mountain, and ZhaMasheke) in the HRB at the monthly and daily Nash-Sutcliffe efficiency ranges of 0.75-0.95 and 0.58-0.78, respectively, which are much higher than corresponding efficiency statistics achieved with CFSR (monthly: 0.32-0.49 and daily: 0.26 – 0.45). The CMADS dataset is available free of charge and is expected to a valuable addition to the existing climate reanalysis datasets for deriving distributed hydrologic modeling in China and other countries in East Asia.

Traditional concrete pavements have poor water permeability, while the strength of pervious concrete pavements is low. To solve these problems, this study designed Innovative recycled aggregate pervious concrete (I-RAPC) with controllable water permeability and high strength by using response surface methodology, and investigated the effects of different pore parameters (number, diameter, material, distribution form, etc.) on the performance of I-RAPC. And the strength discount factor method was proposed to construct the theoretical calculation model of compressive strength and pipe pore parameters, and the calculation model of water permeability coefficient was established at the same time. The results show that the fewer the number of holes and the smaller the pipe diameter of I-RAPC, the higher its compressive strength and the smaller the water permeability coefficient. The theoretical model of compressive strength can accurately evaluate the discounting effect of the pore parameters on the compressive strength of I-RAPC, and the maximum relative error is only 7.52%, and the maximum relative error of the calculation model of water permeability coefficient is only 4.42%. I-RAPC has the advantages of high strength and permeability with controllable performance, which overcomes the problems of random distribution of pore space, uncertainty of water permeability, and strength of ordinary pervious concrete.

Revealing the spatial distribution mechanism of the coupling effect between soil water and salt is essential for managing saline-alkali farmland. This study utilized the multifractal method to analyze soil water and salt under varying water content levels in arid saline-alkali farmland. Soil samples were collected on the second (S1), fifth (S2), eighth (S3), eleventh (S4), and fourteenth (S5) days after a rainfall event. The findings showed that a significant decrease in soil water content, contrasting with an increase in soil salt content throughout the soil layers post-rainfall. As water content decreased, the spatial variability of soil water initially increased from S1-3 and then decreased, while the spatial variability of soil salt decreased. The spatial distribution between soil water and salt exhibited a high correlation at S3-4 (with relative water content of soil ranging from 0.52 to 0.75) due to their coupling effect. However, soil salt was unevenly leached by rainfall at high water content levels (S1-2) and precipitated at low water content levels (S5), resulting in low spatial variability correlations between soil water and salt. This study elucidated the coupling process of soil water and salt, identifying their spatiotemporal distribution mechanism in dryland agricultural areas.

The recent availability of commercial platforms for behavioral analysis in zebrafish larvae based on video-tracking technologies has exponentially increased the number of studies analyzing different behaviors in this model organism to assess neurotoxicity. Among the most commonly used assays in zebrafish larvae are basal locomotor activity (BLA) and visual motor response (VMR). However, the effect of different intrinsic and extrinsic factors that can significantly alter the outcome of these assays is still not well understood. In this work we have analyzed in 143 larvae the influence of age (5-8 days post-fertilization), time of day (8:00, 10:00, 12:00, 14:00; 16:00, 18:00, and 20:00 h), and experiment (three experiments performed at different days) on BLA and VMR results (4,004 analyses for each behavior). Results from both behaviors were adjusted to a Random-Effects linear regression model using generalized least squares (GLS), including in the model the effect of the three variables, the second-way interactions between them and the three-way interaction. The results presented in this manuscript show a specific effect of all three intrinsic factors and their interactions on both behaviors, supporting the view that the most stable time period for performing these behavioral assays is from 10:00 am to 04:00 pm, with some differences depending on age of the larva and the behavioral test.

Lake sediment records are of great importance for understanding the evolution of watershed environments. Various studies have been carried out to constrain the depositional ages of lake sediments and examine their physical, chemical, and biological characteristics, aiming to construct historical vegetation, environment and climate patterns in Chinese lake watersheds. In this study, we obtained relevant literature on lake sediment records by searching the key word 'age-depth' from the databases – Web of Science and China National Knowledge Infrastructure (CNKI, the largest Chinese academic database). We analyzed the literature based on its type (published in a Chinese/English journal or as a Master’s/PhD thesis), period of publication, journal (if published in a journal), key authors, study area, dating scale, and main aims. The results suggest that the lakes in the plateau regions are the most popular research topic typically covering 100–200 years (short-term) and 500–30,000 years (long-term). The literature focuses on a wide range of topics, from past environmental evolution in the watershed to lake ecology, and provides a solid foundation for better understanding regional climate change and the preservation of lake environments and ecosystems. In the future, resulting data from environmental reconstruction with lake sediments will be needed to integrate with emerging information processing technologies (e.g., artificial intelligence and meta-analysis), to disentangle the complex interplay between Earth surface processes and global climate change; furthermore, strengthening interdisciplinary collaboration will deepen our comprehension of man-land relationship and promote the sustainable management of lake ecosystems in the context of global climate change.

This study develops a structure for mapping native vegetation in a transition area between Brazilian Cerrado and Atlantic Forest from integrated spatial information from the Sentinel-1 and Sentinel-2 satellites. Most studies use this data separately, however, the integrated use of optical sensors with Synthetic Aperture Radar (SAR) sensors can improve the methodology for classifying land use and land cover (LULC). The fusion of Sentinel-1 and Sentinel-2, for example, can increase the accuracy of mapping algorithms, using complementary information, such as spectral, backscattering, polarimetry, and interferometry. The study area comprises the Lobo Reservoir Hydrographic Basin, which is part of an environmental conservation unit protected by Brazilian law and with significant human development. LULC were classified, using the random forest deep learning algorithm. The classifying attributes were backscatter coefficients, polarimetric decomposition, and interferometric coherence for radar data (Sentinel-1), and optical spectral data, comprising bands in the red edge, near infrared, and shortwave infrared (Sentinel-2). The attributes were evaluated in three settings in which the SAR and optical data were evaluated separately (C1 and C2, respectively) and in an integrated manner (C3). The study found greater accuracy for C3 (96.54%), an improvement of nearly 2% compared to C2 (94.78%) and more than 40% in relation to C1 (55.73%). The classification algorithm encountered significant challenges in identifying wetlandsin C1, but performance improved in C3, enhancing differentiation by stratifying a greater number of classes during training and facilitating visual interpretation during sampling. Accordingly, the use of SAR and optical data becomes an alternative to optimize LULC mapping in tropical regions, due to the limited influence of atmosphere on images in the microwave range.

The Upper Hunter Valley is a major coal mining area containing approximately 40% of the currently identified total coal reserves in New South Wales (NSW), Australia. Due to the ongoing increase of mining activities, PM10 (air-borne particle with an aerodynamic diameter less than 10 micrometres) pollution has become a major air quality concern in local communities. This paper summarises the spatial and temporal variability modes of PM10 pollution in the region, based on long-term multi-site monitoring data and the application of the rotated principal component analysis (RPCA) and wavelet analysis techniques. RPCA identified two distinct air quality clusters/subregions in the valley, one in the west/northwest, the other in the southeast. Wavelet analysis revealed the annual cycle to be most persistent temporal mode of PM10 variability in both subregions, with intermittent signals observed at time scales of around 120, 30~90 and under 30 days. How these variation modes are related to the effects of local PM10 emissions and the influence of meteorology at different time scales deserves further attention in future work. The findings will be used in air quality reporting and forecasting in NSW. The methodology and results can also be useful for air quality research in similar regions elsewhere.

Nitrogen (N) is an essential macro nutrient for crop growth; therefore, N deficit can greatly limit crop growth and production. In the North China Plain (NCP), winter wheat is one of the main food crops, and its yield has increased from approximately 4000 kg ha-1 to 6000 kg ha-1 in the last two decades. Determining the proper N application rates at different growth stages and in all seasons is very important for the sustainable and high production of wheat in the NCP. A field experiment with five N application rates (250, 200, 150, 100, and 40 kgN·ha-1, designated as N250, N200, N150, N100, and N40, respectively) was conducted during the 2017-2018 and 2018-2019 winter wheat seasons to investigate the effects of the N application rate on water- and fertiliz-er-utilization efficiency, and on the crop growth and yield of winter wheat under sprinkler fer-tigation conditions. The results showed that, in the N application range of 40-200 kg ha-1, crop yield and water- and fertilizer-use efficiencies increased as the N application rate increased; however, further increases in the N application rate did not have additional benefits. The N up-take after regreening of winter wheat linearly increased with crop growth. Considering the wheat yield and N-use efficiency, the optimal N application range was 200 kg ha-1, and the best top-dressing strategy was equal amounts of N applied at the regreening, jointing, and grain-filling stages. The results of this study will be useful for optimizing field N management to achieve high wheat yield production in the NCP and in regions with similar climatic and soil environment conditions.

Assessment of extreme events and climate change on reservoir inflow is important for water and power stressed countries. Projected climate is subject to uncertainties related to climate change scenarios and Global Circulation Models (GCMs’). Extreme climatic events will increase with the rise in temperature as mentioned in the AR5 of the IPCC. This paper discusses the consequences of climate change that include extreme events on discharge. Historical climatic and gauging data were collected from different stations within a watershed. The observed flow data was used for calibration and validation of SWAT model. Downscaling was performed on future GCMs’ temperature and precipitation data, and plausible extreme events were generated. Corrected climatic data was applied to project the influence of climate change. Results showed a large uncertainty in discharge using different GCMs’ and different emissions scenarios. The annual tendency of the GCMs’ is bi-vocal: six GCMs’ projected a rise in annual flow, while one GCM projected a decrease in flow. The change in average seasonal flow is more as compared to annual variations. Changes in winter and spring discharge are mostly positive, even with the decrease in precipitation. The changes in flows are generally negative for summer and autumn due to early snowmelt from an increase in temperature. The change in average seasonal flows under RCPs’ 4.5 and 8.5 are projected to vary from -29.1 to 130.7% and -49.4 to 171%, respectively. In the medium range (RCP 4.5) impact scenario, the uncertainty range of average runoff is relatively low. While in the high range (RCP 8.5) impact scenario, this range is significantly larger. RCP 8.5 covered a wide range of uncertainties, while RCP 4.5 covered a short range of possibilities. These outcomes suggest that it is important to consider the influence of climate change on water resources to frame appropriate guidelines for planning and management.

Pea shoots is a popular vegetable in certain regions of the world due to their unique taste and abundance of health-promoting phytochemicals. The perishable nature and susceptibility of root rot of pea shoots necessitate a new soilless production system located close to the market. This study compared the growth of pea shoots using various cultivation methods in LED plant factory. The results showed that early topping (4 days after transplanting, ET) promoted early harvest compared to later topping (20 days after transplanting, LT) and increased the number of harvested shoots by extending the harvest time to 2.8 times, ultimately resulting in a substantial yield improvement. Moreover, the yield of ET with lower planting density (72 plants m-2, ET-LD) was 8.7% higher than ET with higher planting density (126 plants m-2, ET-HD). Particularly, the average fresh weight of individual pea shoots under ET-LD exceeded that of ET-HD by 48.9%. It is advisable to consider adopting ET-LD for the cultivation of pea shoots in LED plant factory. Based on ET-LD, the yield, nutritional quality, and light use efficiency of pea shoots were further explored at different stages under three levels of light intensity (50, 100, 150 μmol m-2 s-1). Contrasted against the light intensity of 50 μmol m-2 s-1, the average fresh weight per pea shoots, number of harvested, and total fresh yield under light intensity of 150 μmol m-2 s-1 treatment increased by 60.2%, 62.8%, and 165.1%, respectively. Meanwhile, the fresh weight per pea shoots, photosynthetic capacity, soluble sugar and vitamin C levels in leaves, as well as light use efficiency and photon yield, initially increased and then decreased with the extension of the planting period. Among these, soluble sugar, LUE, and PY started to decrease after reaching the maximum value at 60-70 days after transplanting. In conclusion, light intensity of 150 μmol m-2 s-1 with a photoperiod of 16 h d-1 using LEDs, combined with early topping within a planting period of 60-70 days, proves to be suitable for the hydroponic production of pea shoots in LED plant factory.

Estimating ground surface PM2.5 with fine spatiotemporal resolution is a critical technique for exposure assessments in epidemiological studies of its health risks. Previous studies have utilized monitoring, satellite remote sensing or air quality modeling data to evaluate the spatiotemporal variations of PM2.5 concentrations, but such studies rarely combined these data simultaneously. We develop a three-stage model to fuse PM2.5 monitoring data, satellite-derived aerosol optical depth (AOD) and community multi-scale air quality (CMAQ) simulations together and apply it to estimate daily PM2.5 at a spatial resolution of 0.1˚ over China. Performance of the three-stage model is evaluated using a cross-validation (CV) method step by step. CV results show that the finally fused estimator of PM2.5 is in good agreement with the observational data (RMSE = 23.00 μg/m^3 and R2 = 0.72) and outperforms either AOD-retrieved PM2.5 (R2 = 0.62) or CMAQ simulations (R2 = 0.51). According to step-specific CVs, in data fusion, AOD-retrieved PM2.5 plays a key role to reduce mean bias, whereas CMAQ provides all-spacetime-covered predictions, which avoids sampling bias caused by non-random incompleteness in satellite-derived AOD. Our fused products are more capable than either CMAQ simulations or AOD-based estimates in characterizing the polluting procedure during haze episodes and thus can support both chronic and acute exposure assessments of ambient PM2.5. Based on the products, averaged concentration of annual exposure to PM2.5 was 55.75 μg/m3, while averaged count of polluted days (PM2.5 > 75 μg/m3) was 81, across China during 2014. Fused estimates will be publicly available for future health-related studies.

The Cauto River Basin (CRB), the heartland of Cuban agriculture, has been hit hard by drought and water shortage. In response to this pressing issue, this study provides a comprehensive as-sessment of water supply, demand and balance within the Cauto River Basin, considering the baseline and projected socio-economic and climatic conditions by coupling of SWAT and WEAP models. The obtained results reveal that the annual flow in the CRB is projected to slightly de-crease (2.5%) in which the reduction in the rainy season (3.1%) is higher than that in the dry sea-son (1.3%). Total water demand in the baseline scenario is around 1.194 billion m3, dominated by agriculture (96%), with rice crop requiring nearly half. For the future scenario of 2050, the study shows a 16.6% surge in demand to 1.394 billion m3, driven by climate change and agricultural expansion. However, domestic use decreases by 10% due to population reduction. Water deficit in the future is projected to increase by 52% from 172.4 to 262.7 million m3 due to rising water demand and declining water supply. This study shows that integrating a hydrological model into a water allocation model is a promising approach to estimate the water supply, demand and balance, which is a crucial component of water resources management.

The fractional advection-dispersion equation FADE plays an important role, especially in explaining the process of solute-transport in natural porous media with different degrees of heterogeneity. However, studies of the flow and transport of contaminants in the underground environment are based on the knowledge of many functional parameters of the subsoil. The delay factor caused by nonlinear absorption is one of these parameters inheriting significant ambiguities in its estimation in heterogeneous media. In the study, a fractional advection-dispersion FADE model was developed by the implicit Euler method, based on a Grunwald and Caputo-Liousville approximation to explicitly evaluate and simulate the transport mechanism of contaminants in media with unsaturated porous materials subjected to a nonlinear sorption model. Better solute mass retention was observed for fractional advection-dispersion FADE model. Moreover, the absorption parameter of the retardation coefficient has a better impact on the motion of the solute in a saturated porous medium. In other words, it has a significant effect on the dispersion of pollutants in aquifers. This study highlights the need to characterize the aquifer to predict solute transport in porous media.

Mangrove ecosystems are one of the most productive on our planet but have declined globally by 30-50%. Many species rely on mangrove habitat and thus their conversion to aquaculture farms has led to a noticeable loss in commodities such as wild fish stocks. This study aimed to assess 1) the influence of the presence of aquaculture and 2) restoration projects on the ecosystems ability to provide resources. We collected data on mangrove vegetation (i.e., biomass, richness and abundance), soil nutrients (i.e. organic carbon, aluminium and nitrogen), crab abundance and fishing pressure in six sites. We set up 15 plots in each site and collected data between May and July 2023. Via generalised linear mixed models we found that the abundance and richness of crabs was significantly higher in aquaculture plots than in no aquaculture plots. Aquaculture plots had higher topsoil aluminium, topsoil and subsoil Nitrogen, and had lower topsoil Carbon than non-aquaculture sites. Restored sites had less Nitrogen in the topsoil than unmanaged sites. Biomass did not change between aquaculture, restored and unmanaged plots. We found a negative correlation between crab abundance and richness and mangrove DBH, suggesting that the species of crabs present preferred areas with propagules for feeding (e.g., Grapsidae crabs). The content of nitrogen in the subsoil was positively correlated with mangrove richness, diversity and height, suggesting the importance of nitrogen availability for mangrove growth. The content of aluminium in the subsoil was negatively correlated with the content of organic carbon both in topsoil and subsoil, suggesting the detrimental effect of aluminium on the carbon cycle. Fishing practices were observed in all sites during the data collection period. Even if most of the vegetation parameters were not significantly affected by presence of aquaculture or management for restoration, it is clear that important variables such as aluminium carbon, and nitrogen content in the soil and crab assemblages were highly variable.

In the present work report, the MgAl₂O₄and the Ag/MgAl₂O₄ samples were successfully synthesized by the modified hydrothermal and the isovolumetric impregnation methods, respectively. The structural properties of the prepared samples were systematically characterized by XRD, SEM, TEM, DRS, XPS and et al techniques. The photocatalytic degradation of methylene blue by the Ag/MgAl₂O₄ and MgAl₂O₄ samples was comparatively studied under UV lamp irradiation. The results revealed that the prepared Ag/MgAl₂O₄ (pH=6) samples were the most active among the samples in photocatalytic of methylene blue. Under UV lamp irradiation, the Ag/MgAl₂O₄ (pH=6) photodegradation of methylene blue reached to 89.6% within 120 min. And the Ag/MgAl₂O₄ (pH=6) complex photocatalysts displayed a high photochemical stability under repeated irradiation. Repeated irradiate the Ag/MgAl₂O₄ (pH=6) compound, which indicated it had a high photochemical stability.

Digital twins are an emerging technology that could be harnessed for the digitalization of the industry. Steel industry systems contain a large number of electro-hydraulic components, as proportional valves. An input-output model for a novel water proportional cartridge valve is derived from physical modelling based on fluid mechanics, dynamics, and electrical principles. The valve is a two-stage valve with two 2/2-way water proportional valves as the pilot stage and a marginally stable poppet-type cartridge valve as the main valve. The orifice equation, which is based on Bernoulli principles, is approximated by a polynomial which makes parameter estimation easier and makes modelling possible without measuring pressure of the varying control volume situated in the pilot stage part of the valve. Data were collected when the valve was operating as a component in a closed-loop system as part of a press-mill machine in a steel manufacturing plant. Parameter estimation was made by convex optimization with physical constraints to overcome problems caused by poor system excitation. For comparison, a simple linear model was derived and the least squares method used for parameter estimation. A thorough estimation of the parameters relative errors is presented. The model contains 5 parameters related to the design parameters of the valve. The modelled position output is in good agreement with experimental data for training and test data. The model can be used for real time monitoring of the valve’s status by the model parameters. One of the model parameters varies linearly with production cycles. Thus, aging of the valve can be monitored.

Researches on the runoff and sediment reduction effects of soil and water conservation measures are being on the rise, which is of great significance for carrying out strategic on soil and water conservation in the Yellow River Basin. Through the analysis of various soil and water conserva-tion measures, runoff, sediment, and rainfall datas in the Sanchuan River Basin from 1960 to 2019, we use the lagrange multiplier method to determining the threshold year of soil and water con-servation measures on runoff and sediment processes. The preliminary conclusion is as follows: The trend of flood season rainfall and annual rainfall in the Sanchuan River Basin is consistent. The 10-year average rainfall in each periods indicates that before 2000, it gradually decreased and then significantly increased. The 10-year average runoff showed a gradual decrease before 2010, followed by a sudden increase, while the 10-year average sediment has shown a decreasing trend years by years, especially after the centralized treatment period. Terrace and dam measures show a trend of first decreasing, then increasing, and then approaching stability during different treat-ment periods, while the trend of forest and grass measures is slightly decreasing and then in-creasing rapidly. The runoff and sediment reduction effects of various soil and water conservation measures during different treatment periods indicate that the runoff reduction effect reached its peak in 2005, while the sediment reduction benefit reached its best in 2015. Based on the compre-hensive benefits of runoff and sediment regulation, 2015 are considered as the threshold year for various soil and water conservation measures, with each measure areas being 4.86 × 104, 17.91 × 104, 1.20 × 104, and 0.83 × 104hm2, respectively. The research results will have certain reference significance for the high-quality development of soil and water conservation in the Yellow River Basin.

Resection of malignant lesions in the oral and maxillofacial area causes functional and morphological defects. To recover from these defects, reconstruction surgery is needed such as a primary closure or a flap. There are advantages and disadvantages to the method of using the primary closure and the flap, and the choice of procedure is entirely up to a surgeon. The purpose of this study is to evaluate availability of primary closure in patients. For 10 years from January 2010 to May 2020, patients who recovered using flaps after removing malignant lesions from the oral cavity and those who closed the lesion using primary closure were investigated. The investigation was conducted by searching the database of the hospital. There were 85 patients who removed malignant lesions in the oral and maxillofacial area, and among them 16 patients closed the soft tissue defects using primary closure. Operation time, histologic types, stages, wound status, and period of hospitalization according to the patients' medical records were investigated retrospectively. Between the staging and the primary closure, statistically significant differences were observed between stage I and stage II patients in 13 patients using the primary closure. (P=0.046). Statistically significant differences were identified between operation time and primary closure, with an average of 4.02 hours (P=0.015). The average period of hospitality for patients who underwent primary closure was 13.4 days, compared to 26.7 days for those who underwent flap surgery. This difference was statistically significant (P=0.0003). This study evaluated the use of primary closure in patients who underwent resection of malignant lesions in the oral and maxillofacial area. Although the majority of patients underwent reconstruction with flaps, our results showed that primary closure can be a viable option for certain patients with early-stage lesions. Therefore, oral and maxillofacial surgeons should carefully consider various evaluation criteria and select appropriate reconstruction methods to optimize functional and aesthetic outcomes for each patient.

Salinity, resulting from climate change and excessive mineral fertilization, burdens farmers and negatively impacts soil and water ecosystems in the Northeastern Nile Delta. Organic and biological approaches are crucial for addressing these issues. This study examined the effects of individual and combined inoculations with cyanobacteria, yeast, and Arbuscular Mycorrhizal Fungi (AMF), with or without K-humate, on enhancing salinity tolerance, increasing yield, and improving crop quality of wheat and faba bean. The aim was to reduce NPK mineral fertilizer application rates to 25% of recommended doses. An economic evaluation was also conducted. In a preliminary laboratory experiment, the interactive effects of these microbiomes on the production of plant antioxidant enzymes and soil enzymes were investigated under salinity stress. Results showed that co-inoculation, especially with K-humate, yielded superior outcomes compared to individual inoculations. The laboratory experiment findings were confirmed by a field trial conducted in saline-alkaline soil in the Northeastern Nile Delta region. The study found that the integrated inoculation of cyanobacteria, yeast, and mycorrhizae with K-humate, along with 25% mineral NPK fertilization enhanced microbial activity, including AMF colonization, spore density, and total bacteria, cyanobacteria, and yeast counts in the plant rhizosphere. It also increased soil enzyme activity, improving soil fertility compared to individual or mineral control treatments. This integration resulted in wheat yields of 2.77 tons/ha and faba bean yields of 4.75 tons/ha. Crop quality improved, with higher levels of nitrogen, potassium, phosphorus, and protein in wheat grains and faba bean seeds. Microbiomes inoculation increased potassium uptake over sodium, enhancing the potassium/sodium ratio and salt stress tolerance. This approach reduces reliance on costly mineral fertilizers by up to 75%, enabling economically viable cultivation in marginal lands. These sustainable practices optimize resource utilization, maximize economic efficiency, and preserve natural resources.

In arid and semi-arid regions like Tunisia, irrigation water is typically saline, posing a soil and crop salinization risk and yield reduction. This research aims to study the combined effects of soil matric and osmotic potential stresses on tomato root water uptake. Plants were grown in pot and field experiments in loamy-clay soils and were irrigated with three different irrigation water qualities: 0, 3.5, and 7 dS/m. The Hydrus-1D model was used to simulate the combined dynamics of subsurface soil water and salts. Successful calibration and validation of the model against measured water and salt profiles enabled the examination of the combined effects of osmotic and matric potential stresses on root water uptake. Relative yields, indirectly estimated from actual and potential transpiration, indicated that the multiplicative stress response model effectively simulated measured yields and the impact of saline water irrigation on crop yields. The gradual salinization of the root zone further evidenced this effect. The scenario considering a temperature increase of 2°C had no significant impact on crop yields in the pot and field experiments.

In order to improve contrast and restore color for underwater image captured by camera sensors without suffering from insufficient details and color cast, a fusion algorithm for image enhancement in different color spaces based on contrast limited adaptive histogram equalization (CLAHE) is proposed in this article. The original color image is first converted from RGB color space to two different special color spaces: YIQ and HSI. The color space conversion from RGB to YIQ is a linear transformation, while the RGB to HSI conversion is nonlinear. Then, the algorithm separately operates CLAHE in YIQ and HSI color spaces to obtain two different enhancement images. The luminance component (Y) in the YIQ color space and the intensity component (I) in the HSI color space are enhanced with CLAHE algorithm. The CLAHE has two key parameters: Block Size and Clip Limit, which mainly control the quality of CLAHE enhancement image. After that, the YIQ and HSI enhancement images are respectively converted backward to RGB color. When the three components of red, green, and blue are not coherent in the YIQ-RGB or HSI-RGB images, the three components will have to be harmonized with the CLAHE algorithm in RGB space. Finally, with 4 direction Sobel edge detector in the bounded general logarithm ratio operation, a self-adaptive weight selection nonlinear image enhancement is carried out to fuse YIQ-RGB and HSI-RGB images together to achieve the final fused image. The enhancement fusion algorithm has two key factors: average of Sobel edge detector and fusion coefficient, and these two factors determine the effects of enhancement fusion algorithm. A series of evaluate metrics such as mean, contrast, entropy, colorfulness metric (CM), mean square error (MSE) and peak signal to noise ratio (PSNR) are used to assess the proposed enhancement algorithm. The experiments results showed that the proposed algorithm provides more detail enhancement and higher values of colorfulness restoration as compared to other existing image enhancement algorithms. The proposed algorithm can suppress effectively noise interference, improve the image quality for underwater image availably.

This study investigates the concentrations of physicochemical and heavy metal contaminants in the groundwater of the Middle Awash Basin, Ethiopia, to inform targeted water management strategies. A total of 32 groundwater samples were collected from 16 stations via piezometers and boreholes at the end of both the dry (June 2021) and wet (October 2021) seasons. Utilizing Inductively Coupled Plasma Mass Spectrometry (ICP-MS), Atomic Absorption Spectroscopy (AAS), and in situ metering, 22 physicochemical and 24 heavy metal parameters were analyzed. The data revealed significant levels of contamination; notably, sample GW11 had extraordinarily high concentrations of total dissolved solids (10,826 mg/L), strontium (908 µg/L), molybdenum (802.4 µg/L), zinc (6060 µg/L), and electrical conductivity (15,645 µS/cm), while GW12 exhibited elevated levels of aluminum (2615 µg/L), zinc (4446 µg/L), and arsenic (117.2 µg/L). Contaminants such as arsenic, vanadium, gallium, lithium, rubidium, chromium, manganese, copper, and zinc were found enriched in groundwater near Lake Beseka, influenced by agricultural runoff from sugarcane plantations and agro-industry activities. Over half of the groundwater sources were unsuitable for drinking, posing significant health risks to local communities that rely heavily on these sources due to limited access to clean surface water. The findings emphasize the urgent need for comprehensive groundwater management and remediation plans in the Middle Awash region to ensure safe and sustainable water use, particularly addressing the variation in contamination levels influenced by Lake Beseka. These measures are critical to protect public health and support local development in the face of ongoing environmental and anthropogenic pressures.

This paper is devoted to the study of multi-dimensional integral transform with Fox H-function in the kernel in weighted spaces integrable functions in the domain R+n with positive coordinates. Mapping properties such as the boundedness, the range, the representations of the considered transformation are established.

Climate change is likely to have a complex effect on the growth of plants, their phenology, plant-pollinator interactions, and reproductive success. Therefore, we tested the impact of three key factors (temperature, water, and nitrogen supply) on traits, pollination, and seed production in Sinapis alba (Brassicaceae). We grew the plants in different combinations of temperature, water, and nitrogen supplementation, measured multiple vegetative and floral traits, and assessed the response of pollinators in the field. We also evaluated the effect of growing conditions on seed set in plants exposed to pollinators and hand-pollinated plants. Our results show that water stress impaired vegetative growth, decreased flower production, reduced visitation by pollinators and seed set, while nitrogen availability played an important role in nectar production. Temperature modulated the effect of water and nitrogen availability on vegetative and floral traits and strongly affected flowering phenology and flower production. We demonstrated that changes in temperature, water, and nitrogen availability induce changes in plant vegetative and floral traits which impact flower visitation and consequently plant reproduction. Climate change, particularly increasing temperature combined with reduced precipitation, thus may impact plant-pollinator interactions with negative consequences for the reproduction of wild plants and insect-pollinated crops.

Rising organic charge in northern freshwaters is attributed to increasing levels of Dissolved Natural Organic Matter (DNOM) and shifts in water chemistry. Organic charge concentration may be determined by charge balance calculations (Org.-) or modelled (OAN-) using the conceptual Oliver and Hruška models based on the density of weak acid functional sites (SD) present in DNOM. The charge density (CD) is governed by the SD and protonation and complexation reactions on the functional groups. The models use this SD as a key parameter in empirically fitting the model to Org.-. Utilizing extensive datasets of water chemistry, this study shows that spatial and temporal differences in SD and CD are influenced by variations in the humic-to-fulvic ratio of DNOM and the organic aluminum (Al) complexation, as well as the mole fraction of CD to SD governed by the acidity. Site median SD obtained for 44 long-term monitored acid-sensitive lakes was 11.1 and 13.9 µEq/mg C for the Oliver and the Hruška model, respectively. During the 34 years of monitoring the CD increased by 70%, likely due to rising pH and declining Al complexation with DNOM. Present-day median SD values for the Oliver and Hruška models in 16 low-order streams are 13.8 and 15.8 µEq/mg C, respectively, and 10.8 and 12.5 µEq/mg C, respectively, in 10 high order rivers.

In contrast to “frank” pathogens, like Salmonella entrocolitica, Shigella dysenteriae, and Vibrio cholerae, that always have a probability of disease, “opportunistic” pathogens are organisms that cause an infectious disease in a host with a weakened immune system and rarely in a healthy host. Historically, drinking water treatment has focused on control of frank pathogens, particularly those from human or animal sources (like Giardia lamblia, Cryptosporidium parvum, or Hepatitis A virus), but in recent years outbreaks from drinking water have increasingly been due to opportunistic pathogens. Characteristics of opportunistic pathogens that make them problematic for water treatment include: 1) they are normally present in aquatic environments, 2) they grow in biofilms that protect the bacteria from disinfectants, and 3) under appropriate conditions in drinking water systems (e.g., warm water, stagnation, low disinfectant levels, etc.) these bacteria can amplify to levels that can pose a public health risk. The three most common opportunistic pathogens in drinking water systems include Legionella pneumophila, Mycobacterium avium, and Pseudomonas aeruginosa. This report focuses on these organisms to provide information on their public health risk, occurrence in drinking water systems, susceptibility to various disinfectants and other operational practices (like flushing and cleaning of pipes and storage tanks). In addition, information is provided on a group of nine other opportunistic pathogens that are less commonly found in drinking water systems, including Aeromonas hydrophila, Klebsiella pneumoniae, Serratia marcescens, Burkholderia pseudomallei, Acinetobacter baumannii, Stenotrophomonas maltophilia, Arcobacter butzleri, and several free-living amoebae including Naegleria fowleri and species of Acanthamoeba. The public health risk for these microbes in drinking water is still unclear, but in most cases, efforts to manage Legionella, mycobacteria, and Pseudomonas risks will also be effective for these other opportunistic pathogens. The approach to managing opportunistic pathogens in drinking water supplies focuses on controlling the growth of these organisms. Many of these microbes are normal inhabitants in biofilms in water, so the attention is less on eliminating these organisms from entering the system and more on managing their occurrence and concentrations in the pipe network. With anticipated warming trends associated with climate change, the factors that drive the growth of opportunistic pathogens in drinking water systems will likely increase. It is important, therefore, to evaluate treatment barriers and management activities for control of opportunistic pathogen risks. Controls for primary treatment, particularly for turbidity management and disinfection, should be reviewed to ensure adequacy for opportunistic pathogen control. However, the major focus for the utility’s opportunistic pathogen risk reduction plan is the management of biological activity and biofilms in the distribution system. Factors that influence the growth of microbes (primarily in biofilms) in the distribution system include, temperature, disinfectant type and concentration, nutrient levels (measured as AOC or BDOC), stagnation, flushing of pipes and cleaning of storage tank sediments, and corrosion control. Pressure management and distribution system integrity are also important to the microbial quality of water but are related more to the intrusion of contaminants into the distribution system – rather than directly related to microbial growth. Summarizing the identified risk from drinking water, the availability and quality of disinfection data for treatment, and guidelines or standards for control showed that adequate information is best available for management of L. pneumophila. For L. pneumophila the risk for this organism has been clearly established from drinking water, cases have increased worldwide, and it is one of the most identified causes of drinking water outbreaks. Water management best practices (e.g., maintenance of a disinfectant residual throughout the distribution system, flushing and cleaning of sediments in pipelines and storage tanks, among others) that have been shown to be effective for control of L. pneumophila in water supplies. In addition, there are well documented management guidelines available for the control of the organism in drinking water distribution systems. By comparison, management of risks for Mycobacteria from water are less clear than for L. pneumophila. Treatment of M. avium is difficult due to its resistance to disinfection, the tendency to form clumps and attachment to surfaces in biofilms. Additionally, there are no guidelines for management of M. avium in drinking water and one risk assessment study suggested a low risk of infection. The role of tap water in the transmission of the other opportunistic pathogens is less clear and in many cases actions to manage L. pneumophila (e.g., maintenance of a disinfectant residual, flushing, cleaning of storage tanks, etc.) will also be beneficial in helping to manage these organisms as well.

The Lower Mekong Basin has had extensive hydropower dam development, which changes hydrologic conditions and threatens the exceptional aquatic biodiver-sity. This study quantifies the degree of hydrologic change between pre-impact (1965-1968) and post-impact (2018-2021) peak hydropower development in two major tributaries of the Lower Mekong Basin, the Sekong River with the fewest dams and the Sesan River with the most dams. Both rivers historically supported migratory fishes. We use daily pre- and post-impact data and the Indicators of Hydrologic Alteration framework to evaluate streamflow changes from dam development. We found signifi-cant changes in low and high magnitude flows in the pre- and post-impact periods of dam development. For the Sekong River, minimum flow had large fluctuations that ranged 290% to 412% more than the pre-impact period, while the Sesan River ranged 120% to 160% more than pre-impact. Dry season flows increased by 200±63% on av-erage in the Sekong River, which is caused by releases from upstream dams. Mean-while, Sesan River dry season flows increased by 100±55% on average. This study in-dicates that seasonal flow changes and extreme flow events occurred more frequently in the two basins following dam construction, which may threaten the ecosystem func-tions.

Leakage is important in groundwater cycle research and water resource management, the key is to construct the spatial distribution of aquitard. Influenced by natural and anthropogenic factors, the density of boreholes restricts the accuracy of aquitard structure. This paper explores the K-Nearest Neighbor (KNN) method to construct multi-layer aquitard structure in the hinterland of Songnen Plain, Northeast China, with limited boreholes, and compare it with Inverse Distance Weight (IDW) and Ordinary Kriging (OK) methods to evaluate the leakage. The KNN needs to first identify the eigenvalue-k of each layer, which is used to enhance the trainset to obtain the testset with a larger amount of sample data enhanced, and to make a prediction to obtain the 3-dimensional structure of aquitard. KNN is more accurate than the IDW and OK. The aquitrad structure obtained by the KNN is different from the IDW and OK, the thickness difference is 3.53%-54.00%, the area difference is 2.28%-23.91%, and the difference in leakage can be up to 24.51%. KNN also has a high degree of identification of aquitard edges, which can help the prevention of groundwater pollution. The results provide guidance for water balance analysis, borehole engineering design, water resources management and exploitation.

Considering characteristics of high river density, special underlying surface in plain river network region, and municipal drainage system function, river network drainage unit model is proposed, which is defined as a region surrounded by main river or embankment. Flood storage variety and control projects regulation of small rivers in each unit is simulated. With drainage catchment as an object, according to its drainage capacity, simplified municipal drainage model was developed. Coupling river network drainage unit model, simplified municipal drainage model and 2D flood routing model, urban flood analysis model for plain tidal river network region was developed, which could be applied to analyzing flood from upstream river, storm surge and local rainfall. Demonstration research was carried out in Puxi flood protected area in Shanghai.

In this study, the effects of grain size and gradation of riprap, overtopping flow depth and downstream slope of embankment on scouring and deposition characteristics at the downstream toe of the embankment was investigated. For the experiment, three different downstream slopes (1:2, 1:3, and 1:4), three different overflow depths (1, 2, and 3 cm), and three different sizes (d₅₀ of 16.41 mm, 8.48 mm, and 3.39 mm herein referred as No.5, 6 and 7 respectively) of riprap particles, respectively, were used in the laboratory. The experimental results demonstrated that the scour depth and deposition height increased with increasing energy head for each downstream slope condition. Among the three particle sizes, for No. 5 size particle shows the lowest scour depth and highest deposition height. For the 1:2 slope, the No. 5 particle size could resist scour 62% and 75% less than that of the No. 6 and No. 7 particles, respectively. For the 1:3 slope case, this was 31% and 46%, and for the 1:4 slope case, this was 39% and 49% less than the No. 6 and No. 7 size particles, respectively.

The main target of this study was to evaluate the impact of future climate change on the available surface water resources in the Dhidhessa Sub-basin, Abbay Basin, Ethiopia. For the prediction, high-resolution Regional Climate Models (RCMs) from multiple climate models with data from Representative Concentration Pathways (RCPs) prepared by the CCAFS were used. The predictions of future discharge (stream flow) were based on climate scenarios data of baseline period of 1991 to 2020 and for the future with two time windows, 2044 (2030–2059) and 2084 (2070–2099), on a monthly time step after bias correction was conducted to both precipitation and temperature in the future climate under each RCP scenario. After sensitivity analysis, calibration (1994–2011), and validation (2012–2020) of the model for the Dhidhessa Sub-basin with the SUFI-2 program in the SWAT-CUP model, the SWAT model was used to determine water balance and stream flow from the SWAT model system. The SWAT model performed well in predicting stream flow in the Dhidhessa Sub-basins, with a coefficient of determination (R2) ranging from 0.8 to 0.94 and a Nash Sutcliffe value (NSE) ranging from 0.76 to 0.89. The percent decrease in mean annual stream flow from 2044 and 2084 were 10 %, in 2044, and 6.3% in 2084 respectively. The seasonal result under short-term 2044 of stream flow present change significantly decreased in spring, winter, and autumn with 20.2%, 67.4%, and 67.4% respectively. While summer season increased by 43.1%, under short-term 204. In long-term 2084 percent change declined except summer seasons, with 14.7%, 58.1%, and 3.3%, change in spring, winter, and autumn, respectively, and summer, with 51.1% increased and With RCP4.5 (1.64%) and RCP8.5 (2.1%) changed. In the future Dhidhessa stream flow increases and decreases from the baseline era. The decreasing stream flow in 2044 and 2084 will negatively affect agricultural production. This study revealed that any effect on this river resulting in a drop in flow will have a direct impact on ongoing water resource development and socio-economic development of the area.

Conditions under which compositions of component systems form a well-defined system-of-systems here are formulated at a fundamental level. Statement of what defines a well-defined composition and sufficient conditions guaranteeing such a result offers insight into exemplars that can be found in special cases such as differential equation and discrete event systems. For any given global state of a composition, two requirements can be stated informally as: 1) the system can leave this state, i.e., there is at least one trajectory defined that starts from the state, and 2) the trajectory evolves over time without getting stuck at a point in time. Considered for every global state, these conditions determine whether the resultant is a well-defined system and if so, whether it is non-deterministic or deterministic. We formulate these questions within the framework of iterative specifications for mathematical system models that are shown to be behaviorally equivalent to the Discrete Event System Specification (DEVS) formalism. This formalization supports definitions and proofs of the afore-mentioned conditions. Implications are drawn at the fundamental level of existence where the emergence of a system from an assemblage of components can be characterized. We focus on systems with feedback coupling where existence and uniqueness of solutions is problematic.

The bivalve mollusc Pinna nobilis, endemic to the Mediterranean Sea, since 2016 is vanishing from the whole basin because of an infection by multiple pathogens that caused mass mortality events. In the Eastern Mediterranean some little populations seem to be resistant to the infection. These individuals could represent the only possibility for the species to recolonize now desert habitats. Thus, according to the recommendations of IUCN, the looking for living specimens of P. nobilis is a priority. As a result of a monitoring activity carried out in 2022-2024, along the Ionian cost of Apulia, in Southern Italy, the species has completely disappeared leaving only empty shells. Concurrent to the vanishing of P. nobilis, its congeneric P. rudis, resistant to the infection, seems to be taking advantage, becoming more common and colonizing habitats once exclusive of P. nobilis. In fact, from different areas of the Mediterranean, the sightings of P. rudis are increasing, together with the discovering of individuals exhibiting morphological traits that are a mixing between the two species. In some cases, these morphological features are not easy to detect, anyway the presence of these hybrids, resistant to the infection, is important for the conservation of the species.

In the era of mounting water scarcity, particularly in arid regions, the agricultural sector is striving to optimize the water resource management practices. Treated wastewater (TWW) has emerged as a viable alternative to freshwater for irrigation, offering a sustainable solution to water conservation. However, ensuring the safety and quality of TWW is paramount to safeguard for both crop health and environmental integrity. Electrical conductivity (EC), a critical factor in assessing TWW suitability for irrigation, can significantly impact crop yields and soil health since it is directly linked to the concentration of dissolved salts and ions. Therefore, this study delves into the development of advanced predictive models for EC assessment by employing supervised machine learning (ML) techniques like the Support Vector Regression (SVR), Adaptive Network-based Fuzzy Inference System (ANFIS), and Multiple Linear Regression (MLR). The TWW samples collected from Al-Qatif area, Saudi Arabia were assessed in the lab through a sensor-based real-time monitoring system integrated with Internet of Things (IoT) network and a multiprobe device. The key water quality parameters assessed involved, temperature (T), pH, Oxidation Reduction Potential (ORP), Resistivity (RES), Total Dissolved Solids (TDS), Salinity and Turbidity which served as the foundation for these models, given their profound influence on and their anticipated impact on EC levels. Following feature selection, two distinct model combinations were identified for the SVR, ANFIS and MLR models. Furthermore, to evaluate prediction performance, four statistical criteria, including coefficient of determination (R²), correlation coefficient (R), mean square error (MSE), and root mean square error (RMSE), were employed. Overall, the comparative performance results proved that ANFIS-M2 indicated the strongest predictive capability with the R² value of 0.99572 and 0.75145 and the RMSE values of 0.00965 and 0.01134, respectively in both calibration and verification stages.

The field of water management is continually changing. Water has been subject to external shocks in the form of climate change and globalization. Analysis of water management is subject to disciplinary developments and inter-disciplinary interactions. Are these developments well documented in the literature? Initial observations on interdisciplinary literature suggest that results are fragmented, implying that a state-of-the-art review is needed. The objective of this paper is to close this gap by reviewing recent developments in water economics that address the increasing perceptions of water scarcity by looking first at changes in supply and quality of water, and then at impacts of climate change on water extremes. Among responses to such challenges, the paper identifies changes to water use patterns by including and co-managing water from different sources—surface and groundwater, wastewater, and desalinated water. Technological advancements also are among the resources that address water challenges. Water challenges reflect also on management of internationally shared water. A recent surge in scientific work identified international treaties as playing a significant role in water management. The paper reviews recently employed economic tools, such as experimental economics, game theory, institutional economics, and valuation methods. And finally, it explores modeling approaches, including hydro-economic and computable general equilibrium models that are being used to deal with water challenges.

Adaptation to climate change is being addressed in many domains. This means that there are multiple perspectives on adaptation; often with differing visions resulting in disconnected responses and outcomes. Combining singular perspectives into coherent, combined perspectives that include multiple needs and visions can help to deepen the understanding of various aspects of adaptation and provide more effective responses. Such combinations of perspectives can help to increase the range and variety of adaptation measures available for implementation or avoid maladaptation compared with adaptations derived from a singular perspective. The objective of this paper is to present and demonstrate a framework for structuring the local adaptation responses using the inputs from multiple perspectives. The adaptation response framing has been done by: (i) contextualizing climate change adaptation needs; (ii) analyzing drivers of change; (iii) characterizing measures of adaptation; and (iv) establishing links between the measures with a particular emphasis on taking account of multiple perspectives. This framework was demonstrated with reference to the management of flood risks in a case study Can Tho, Vietnam. The results from the case study show that multiple perspective framing of adaptation responses enhance the understanding of various aspects of adaptation measures, thereby leading to flexible implementation practices.

Channel bends are one of the most important characteristic features of natural streams. These bends often create the conditions for a hyporheic zone, which has been recognized as a critical component of stream ecosystems. The streambed vertical hydraulic conductivity (K_v), vertical hydraulic gradient (VHG) and Darcian flux (DF) in the hyporheic zone were estimated at 61 locations along a channel bend of the Beiluo River during July 2015 and January 2016. All the streambed attributes showed great spatial variability along the channel bend. Both upward fluxes and downward fluxes occurred during the two test periods, most of studied stream sections were controlled by downwelling, indicating stream water discharge into the subsurface. The average downward flux was higher at the downstream side than at the upstream side of the channel bend, especially in July 2015. The distribution of streambed sediment grain size has a significant influence on the variability of K_v; high percentages of silt and clay sediments generally lead to low K_v values. Higher K_v at the depositional left bank at the upstream site shifted toward the erosional right bank at the downstream site, with K_v values positively correlated with the water depth. This study suggested that the variabilities of K_v and VHG were influenced by the stream geomorphology and that the distribution of K_v was inversely related, to a certain extent, to the distribution of VHG across the channel bend. K_v and VHG were found to have opposite effects on the DF, and the close relationship between K_v and DF indicated that the water fluxes were mainly controlled by K_v.

Crop production in Afghanistan suffers from limited phosphorus (P) availability, which severely hinders national agriculture sustainability. This present study hypothesized that deep fertilizer placement could significantly enhance uptake of immobile P and thus tissue P accumulation and crop yield. A two-year pot experiment growing two maize (Zea mays) hybrid cultivars (Xida-789 and Xida-211) was therefore conducted to test these hypotheses under three contrasting fertilizer placement methods (broadcast, side band, and deep band). In doing so, P concentrations in both maize tissues and soils were compared at 45, 60, and 115 days after sowing (DAS) under nine combinations of nitrogen (N) and P fertilizer rates (kg ha-1: N112P45, N112P60, N112P75, N150P45, N150P60, N150P75, N187P45, N187P60, N187P75). Results have shown that deep band placement significantly increased P uptake efficiency, leading to greater P concentration and accumulation in maize tissues compared to other two fertilization methods. This improved P uptake was attributed to several factors associated with deep placement, including reduced P fixation, enhanced root access to P, and moisture availability for P uptake. Additionally, deep band placement combined with higher N application rates (N187 and N150) further enhanced plant P uptake by promoting P availability and utilization mechanisms. Deep band placement also resulted in significantly higher total soil P, Olsen-P, and P use efficiency than broadcast and side band methods, indicating a more efficient P fertilization strategy for maize that can improve growth and yield. This present study also found positive correlations between P concentration in plant organs and soil Olsen-P, highlighting the importance of adequate soil P levels for optimal plant growth. Overall, our results have showed that deep band fertilizer placement emerged as a superior strategy for enhancing P uptake efficiency, utilization, and maize productivity compared to broadcast and side band placement. This approach can potentially optimize P fertilizer utilization, improve maize growth and yield, while minimizing environmental P losses associated with broadcast applications.

The main purpose of our research is the evaluation of the efficacity of solvent polarity on phenolic composition, as well as the antibacterial, and antioxidant activities of extract of Moroccan Mentha aquatica L., leaves. To attempt these objectives, the HPLC-DAD was used to identify the biomolecules. The total amount of phenolic and flavonoid content was determined using the Folin-Ciocalteu and aluminum trichloride processes as well as the DPPH, RP, and TAC tests were used to evaluate the antioxidant capabilities. In addition, by employing both in vitro and in silico analysis through the microdilution method, the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of the extracts were assessed against multidrug-resistant bacteria. Furthermore, the High-Performance Liquid Chromatography (HPLC) analysis indicated that all extracts of M. aquatica were abundant in noteworthy phytochemical compounds, especially gallic acid, vanillic acid, chlorobenzoic acid, quercetin, and kaempferol. Furthermore, the results indicated that the total phenolic content was higher in hydroethanolic extract (62.19 ± 1.19 mg GAE/g DW) in contrast to the acetonic and aqueous extracts (22.22 ± 0.64, and 22.44± 0.57 mg GAE/g DW) respectively. Similarly, the aqueous ethanol extract contained the greatest flavonoid concentration, with values of 29.15± 0.09 mg QE/g DW when compared with the other extracts. The seam extract poses excellent antioxidant power with an IC50 of 0.06 ± 0.00 mg/mL for the DPPH test, and lower RP with EC50 of 80± 0.00 µg/ml when compared with acetonic and aqueous extract (370± 0.00 and 460± 0.01 µg/mL) respectively. Moreover, the hydroethanolic extract has a high level of TAC 75.09± 2.00 mg EAA/g DW, followed by aqueous extract carrying a value of 28.53 ± 1.36 mg EAA/g DW. The antibacterial capacity is ranged between 0.78 ± 0.05 mg/mL and 12.60 ± 0.00 mg/L. The results of the in-silico study demonstrated that quercetin, vanillic acid, and naringenin components contribute to the antioxidant capability. While gallic acid, kaempferol, and quercetin components are attributed to the antibacterial capacity.

The primary objective of this study was to demonstrate the potential of digital image analysis as a tool to identify microplastic (MP) particles in surface waters and to facilitate their characterisation in terms of 2D and 3D morphology. Digital image analysis preceded by microscopic analysis was used for an exhaustive quantitative and qualitative evaluation of MPs isolated from the Vistula river. Using image processing procedures, 2D and 3D shape descriptors were determined. The Principal Components Analysis (PCA) was used to interpret the relationships between the parameters studied, characterising MP particle geometry, type and colour. This multivariate analysis of the data allowed 3 or 4 main factors to be extracted, explaining approximately 90% of the variation in the data characterising MP morphology. It was found that the first principal component for granules, flakes and films was largely represented by strongly correlated with 2D shape descriptors (area, perimeter, equivalent area diameter) and 3D shape descriptors (CSF, Compactness, Dimensionality). Considering the scraps, PC1 was represented by only five of the above descriptors, and the Compactness variable had the largest contribution to PC2. In addition, for granules, flakes and films, a relationship between 2D shape and the colour of their particles could be observed. For the most numerous MP group identified of multicoloured scraps, no such association was found. The results of our study can be used for further multivariate analysis regarding the presence of microplastic floating on the river surface, with a particular focus on particles of secondary origin. This is of key importance for optimising future efforts in conducting small-scale and multidimensional monitoring of and reducing plastics in the aquatic environment.

In this paper we describe a method which combines sentiment analysis with machine learning techniques and/or multivariate statistical analysis. By applying this methodology it is possible to classify a collection of texts into two or more groups or clusters. On the basis of a number of previously defined clusters, the novelty of the outlined approach is the use of the sentiment analysis results as input to the machine learning model or multivariate statistical analysis. Once the classifier has been obtained, we can assign a given text into one of the pre-established clusters. The groups or clusters can represent different time periods, classes of texts transcribed from different conversations, etc. The method is illustrated through an example taken from one of the two studies in which we have applied this methodology. In one of the studies, the method was used to classify press news of a volcanic eruption, while in the other study it was used to classify the conversations recorded between a chatbot with different kinds of speakers (humans or chatbots). This last study was the seminal work in which we introduced this methodology.

In the context of climate change in West Africa characterized by a reduction of precipitation, this study was conducted to evaluate the impact of climate change on water resources from now to the end of the 21st century in the transboundary watershed of the Sassandra River shared by Guinea and Côte d’Ivoire. Historical and future climate (Representative Concentration Pathways or RCPs 4.5 and 8.5 scenarios) data were projected with the model. The Abdus Salam ICTP RegCM4 was used. The hydrological modeling of the river basin was carried out with the conceptual hydrological model, GR2M. This model is a monthly time steps model that allows the assessment of the discharge of the Sassandra River for each climate scenario according to the 2030 (2021–2040), 2050 (2041–2060), 2070 (2061–2080), and 2090 (2081–2100) horizons. The results showed a reduction of the annual discharge when compared to the baseline (1961–1980). For the RCP 4.5, the observed values went from –1.2% in 2030 to –2.3% in 2070 and rose to –2.1% in 2090. Concerning the RCP 8.5, we saw a variation from –4.2% to –7.9% in the 2030 and 2090 horizons, respectively. With the general decrease of rainfall in West Africa, it is appropriate to assess the impact on water resources on the largest rivers (Niger, Gambia, and Senegal) that irrigate the Sahelo-Saharian zone.

Compound parabolic concentrators are relevant systems used in solar thermal technology. With adequate tailoring, they can be used as an efficient and low-cost alternative in residential water applications. This work presents a simulation study using a ray tracing methodology. With this technique we simulate the interaction between solar rays and solar concentrator to quantify the amount of energy that impinges on the receiver at a particular time. Energy availability is evaluated in a comparison of two configurations: stationary at 21° throughout the year and multi position setup; tilted with respect to the horizontal depending on three seasonal positions: 0° for summer, 16° for spring / autumn and 32° for winter, with the objective of increasing the amount of available energy in each season. The fact that a tracking system can be dispensed with also represents an economical option for the proposed application. The results showed that at 21°, the proposed system works satisfactorily; however, by carrying out the selected angular adjustments, the overall energy availability increased by 22%, resulting in a more efficient option. The methodology developed herein proved to be a valuable tool for prototype design and performance evaluation.

A new type of artificial block is proposed by modifying the traditional block. Based on the physical model experiment, the wave reflection and run-up characteristics of the new ecological blocks under regular waves were examined, and the influence of the height of the "planting trough" border on the hydrodynamic properties was analyzed. The results indicate that the wave reflection and run-up would decrease with a decrease in the breakwater slope. As wave height increases, wave run-up increases, and the reflection coefficient falls. Wave reflection and run-up increase with an increasing wave period. The relative depth of the water has a smaller impact on the wave reflection than the wave run-up. The reflection coefficient of the new ecological blocks is consistently lower than that of the conventional and continues to decrease as the border of the "planting trough" is raised. The raised borders prevent water loss in the trough, resulting in no significant improvement in the wave run-up performance of the new blocks. The reflection coefficient and the relative run-up R/H gradually increase with the average wave breaking parameter ξ increase. The crude permeability coefficients for the new blocks, New Heights 1 and New Heights 2, are 0.53, 0.53, and 0.54, respectively.

This research focuses on the use of the HEC-RAS model to estimate flash flood risk. It combines advanced hydraulic modeling techniques and precise data entry. The aim is to contribute knowledge to assess flash flood risk and reduce impacts on communities and infrastructure. The selection of study areas with a history of severe flooding, such as the Lam Saphung Basin, Phrom River Basin, and Lam Chern River Basin Part 1 in Thailand, highlights the importance of thorough flash flood risk assessment. By leveraging the HEC-RAS model, the results of this research inform proactive risk management strategies, improve emergency preparedness and help develop sustainable mitigation measures. The results are important in developing emergency response strategies and overall recovery ability in areas at risk of flash floods. The research combines advanced hydrologic modeling and real-world flash flood data. In addition to the flood condition assessment, the extent of the flood area and associated hazards were assessed using a two-case simulation strategy. The study covers future scenarios related to land use changes and retrospective analysis of past flood events. The results have practical implications for improving emergency response strategies, land use planning, and overall resilience in flash flood-prone areas. The integrated approach emphasizes the research output to providing insights and actionable solutions for communities facing ongoing challenges posed by flash floods.

Climate simulations in West Africa have been attributed with large uncertainties. Global climate projections are not consistent with changes in observations at the regional or local level of the Niger basin, making management of hydrological projects in the basin uncertain. This study evaluates the potential of using the quantile mapping bias correction to improve the Coupled Model Intercomparison Project (CMIP5) outputs for use in hydrology impact studies. Rainfall and temperature projections from 8 CMIP5 Global Climate Models (GCM) were bias corrected using the quantile mapping approach. Impacts of climate change was evaluated with bias corrected rainfall, temperature and potential evapotranspiration (PET). The IHACRES hydrological model was adapted to the Niger basin and used to simulate impacts of climate change on discharge under present and future conditions. Bias correction significantly improved the accuracy of rainfall and temperature simulations compared to observations. Nash coefficient (NSE) for monthly rainfall comparisons of 8 GCMs to the observed was improved by bias correction from 0.69 to 0.84. The standard deviations among the 8 GCM rainfall data were significantly reduced from 0.13 to 0.03. Increasing rainfall, temperature, PET and river discharge were projected for all GCMs used in this study under the RCP8.5 scenario. These results will help improving projections and contribute to the development of sustainable climate change adaptation strategies.

Environmental monitoring programs rely on periodic spot sampling at specific locations, followed by laboratory analysis, aiming at the evaluation of water quality at a catchment scale. For this purpose, automatic telemetric stations for specific parameters have been installed by the Institute of Marine Biological Resources and Inland Waters of Hellenic Centre for Marine Research (IMBRIW-HCMR) within several Greek rivers and lakes, providing continuous and temporal monitoring possibilities. Nevertheless, the employment of unmanned surface vehicles (USV) equipped with integrated sensors represents a tool valuable to several monitoring strategies, offering enhanced temporal and spatial coverage over specific timeframes, allowing for targeted examination of sites or events of interest. The USVs have been deployed by Athens Water and Sewerage Company (EYDAP) as a cost-effective tool for the environmental monitoring of surface water bodies of interest, with emphasis on the spatial fluctuations of chlorophyllα, electrical conductivity, dissolved oxygen and pH, observed in Koumoundourou Lake and rivers Acheloos, Asopos and Kifissos. The effectiveness of an innovative heavy metal (HM) system installed in the USV for thein situ determination of copper and lead was also evaluated herewith. The results obtained demonstrate that both the timely detection of potential pollution from both anthropogenic activities and natural processes as well as the monitoring of inland waters are made feasible through the employment of USV.

Water scarcity is a worldwide concern, considering that water is a limited resource and essential for life. In Brazil, approximately 30% of its population lives in one of the areas that most suffer from lack of water, the semi-arid region covering about 20% of the country's territorial extension. The lack of water, mainly in the northeast of the country, has been a problem for years, where people who live in this territory have been suffering for months from the lack of water and the poor distribution of the resource, which increases the degree of inequality between the regions of the country. The research aims to show the effect of the hydrological cycle on the quality of vegetation and how such processing can end up affecting people's lives and the environment. The municipality of Floresta is within the scope of sub-basin 73, the territory is part of the municipalities benefited from the PISF- São Francisco River integration project works, and the study has raised discussion on the part of the scientific community regarding the effectiveness of the population project and the possible risks caused to the environment. This study carried out a temporal analysis, 1961-2021, to investigate water availability and how the hydrological system can affect society, raising the degree of its importance for a better quality of life and consequently reducing hydric inequalities. It was also evaluated how climate changes can interfere with these environmental changes and the quality of life at the local scale. The hydrological model system used to assess water availability was the Pernambuco Hydrological Response Units SUPer-System. In addition, this system helped to understand the changes that occurred in the studied sub-basin. Yet was used UAV-Unmanned Aerial Vehicles to view relationship between lives in house and environment conditions. The study can obtain accurate and necessary information to understand the dynamics of the hydrological system and the possible changes of social hydric inequalities. Thus, it is concluded that climate change will have different impacts on small scales and lives conditions due to different characteristic's environment. It is very important to carry out studies on a detailed scale to provide better public policies for mitigating the effects of climate change on people's lives.

Reservoir routing has been a routine procedure in hydrology, hydraulics and water management. It is typically based on the mass balance (continuity equation) and a conceptual equation relating storage and outflow. If the latter is linear, then there exists an analytical solution of the resulting differential equation, which can directly be utilized to find the outflow from known inflow, and to obtain macroscopic characteristics of the process, such as response and residence times, and their distribution functions. Here we streamline the reservoir routing framework and extend it to find approximate solutions for nonlinear cases. The proposed framework can also be useful for climatic tasks, such as describing the mass balance of atmospheric carbon dioxide and determining characteristic residence times, which have been an issue of controversy. Application of the theoretical framework results in excellent agreement with real world data. In this manner, we easily quantify the atmospheric carbon exchanges, and obtain reliable and intuitive results, without the need to resort to complex climate models. The mean residence time of atmospheric carbon dioxide turns out to be no more than four years and the response time is smaller than that, thus opposing the much longer mainstream estimates.

Using a detailed atmospheric radiative transfer model, we derive macroscopic relationships of downwelling and outgoing longwave radiation, useful for hydrological practice. We validate them using empirical formulae based on downwelling radiation data, which are in common use in hydrology, as well as satellite data for the outgoing radiation. We use the macroscopic relationships to infer the relative importance of carbon dioxide and water vapour in the greenhouse effect. The results show that the contribution of the former is 4% – 5%, while water and clouds dominate with a contribution of 87% – 95%. The minor effect of carbon dioxide is also confirmed by the small, non-discernible effect of the recent escalation of atmospheric CO2 concentration from 300 to 420 ppm, which is quantified at 0.5% for both downwelling and outgoing radiation. Water and clouds also perform other important functions in climate, such as regulating the heat storage and the albedo, as well as cooling the Earth’s surface though latent heat transfer, with a contribution of 50%. By confirming the major role of water on climate, these results suggest that hydrology should have a more prominent and more active role in climate research.

This study examines the environmental challenges faced by Malaysian industries in adhering to industrial effluent regulations with the research question, what are the challenges in complying with environmental legislations from industries? It investigates the primary factors contributing to non-compliance and the perspectives, knowledge, and needs of Malaysian industries regarding environmental compliance. This study recommends the best strategy for promoting self-compliance. Thirteen stakeholders from various industries with environmental management experience were interviewed. Over the past seven years, these industries have shown low com-pliance with the Industrial Effluent Regulation 2009, prompting an exploration of their adaptability to regulations. Challenges identified include cost, employee attitudes, technology, management support, public complaints, and jurisdictional issues. Responses varied from divergent to unified viewpoints, highlighting the complexity of compliance issues. Respondents suggested enhancing compliance through behavioral changes, including incentives, enforcement, awareness, guidance, industry ratings, management commitment, and public disclosure of emissions. Suggestions for improvement and innovative solutions emerged based on participants' experiences, emphasizing the importance of continuous improvement. The study emphasizes the government's crucial role in ensuring regulation adherence but underscores the need for analyzing barriers and exploring alternative approaches. Understanding industry perspectives and strategies is essential for progress. Compliance, however, requires an analysis of the current challenges and adopting adaptive measures. It is important to understand industries' perspectives and strategies to move forward.

The impact of antecedent soil moisture content on soil erosion is a complicated phenomenon, which is still under argument with contradictions in research results. Hence, the objective of this study is to investigate the impact of antecedent soil moisture content to soil loss on clay soil by conducting two-year field experiments under natural rainfall on runoff plots with length of 10 meters, width of 3 meters, and uniform slope of 9%. Volumetric soil moisture sensors were used to log soil moisture changes, and soil moisture readings were used along with rainfall records to quantify the antecedent soil moisture conditions for each rainfall event. Results of this study show duration of the effective erosion event outranks the antecedent volumetric soil moisture content. Field study also suggests that accumulative rain falling within 48 hours (Pp48) prior to an effective erosion event strongly correlated with soil loss per Rainfall-Runoff Erosivity Index (Soil Loss / EI30), particularly when the duration of an effective erosion event is either between 3 ~ 7 hours or 10~ 30 hours. Hence, Pp48 can be considered as an alternative to replace antecedent soil moisture content in RUSLE 2’s cover and management factor.

Detecting and monitoring changes in soil salinity through remote sensing provides an opportunity for field assessment in regions where on-site measurements are limited. This investigation, carried out in Siwa Oasis, Egypt, aimed to assess the efficacy of several soil salinity indices derived from Landsat 5 and 7 satellite images. To achieve this, 56 on-site ground measurements were utilized for evaluation purposes. The study aimed to improve the correlation between EC and index values and explore the relationship between salinity and changes in land cover. Eleven spectral indices were calculated for nine scenes captured in different months from August to December. The first approach involved stacking the data to identify the index with the strongest correlation with ground EC values, without the need for complex analysis or EC value ranging. In the second approach, the ground EC measurements were classified into seven different salinity categories, and the correlation coefficient was calculated between each index and each salinity category. The third approach analyzed the data temporally, considering different salinity levels. Lastly, a spatial correlation analysis was conducted between EC and index values in the fourth scenario. The initial approach revealed a weak correlation due to substantial variation in EC values. However, the SI index demonstrated the highest correlation coefficient of 0.38. In the second scenario, the S2 index exhibited the highest correlation of 0.96 for moderate salinity samples. The third scenario showed that the S1 index achieved the highest correlation value of 0.99 for moderately saline areas. In the fourth scenario, the SI index exhibited the strongest correlation among all four ponds with correlation coefficients of 0.23, 0.23, 0.18, and 0.61. Notably, the correlations observed in the second and third scenarios demonstrated higher correlation coefficients compared to both the first and fourth scenarios. The study highlighted significant variations in EC levels related to land cover types and pond elevation. Additionally, remote sensing methods detected a 48% increase in total vegetated area over 17 years, showing the potential of remote sensing techniques in salinity monitoring for expanding agriculture and improving land management.

The escalation of mining activities in the karst regions of Guizhou Province has heightened the occurrence of water-inrush incidents in deep coal mines. This study focused on water-inrush phenomena within the Xinhua mining area of Jinsha County, Guizhou Province, aiming to investigate the sources of these incidents. The findings indicated that the overlying limestone of the Changxing Formation in the coal seam served as a vulnerable aquifer under certain conditions, leading to water inrushes. The analysis of the spatiotemporal distribution patterns of water-inrush incidents at the working face indicated that previous mining operations damaged the shallow Changxing Formation limestone, resulting in the accumulation of goaf water and the formation of numerous mining-induced fractures. These fractures served as rapid conduits for water inrushes from both atmospheric precipitation and underground sources at the deep working face. The examination of surface water and mine water quality demonstrated that both exhibited similar characteristics, predominantly featuring bicarbonate, sulfate, and sodium compositions. Investigation into the relationship between mine water inflow and atmospheric precipitation established that atmospheric precipitation influenced the mine water supply cycle, with a replenishment period of ~10 months during the operational phase of the Jinyuan Coal Mine and about one month post-closure. The fractures induced by mining activities within the Changxing Formation limestone facilitated water flow, with atmospheric precipitation serving as the primary water source for the mine. This study offered a valuable scientific foundation for addressing water-related damage resulting from atmospheric precipitation in mines susceptible to water inrushes under analogous hydrogeological conditions.

Accurate and reliable mid-long runoff prediction (MLTRP) is of great importance in water re-sources management. However the MLTRP is not suitable in each basin and how to evaluate the applicability of MLTRP is still a question. Therefore, the total mutual information (TMI) index is developed in this study based on the predictor selection method using mutual information (MI) and partial MI (PMI). The relationship between the TMI and the predictive performance of five models is analyzed by applying five models in 222 forecasting scenarios in Australia. The results over 222 forecasting scenarios demonstrate that, compared with the MI, the developed TMI index can better represent the available information in the predictors, and has more significant negative correlation with the RRMSE with the correlation coefficient between -0.62 and -0.85. This means the model's predictive performance will become better along with the increase of TMI, and there-fore the developed TMI index can be used to evaluate the applicability of MLTRP. When TMI is more than 0.1, the available information in the predictors can support the construction of MLTRP models. In addition, the TMI is used to partly explain the difference of predictive performance among five models. In general, the complex models, which can better utilize the contained infor-mation, are more sensitive to the TMI, and have more significant improvement in terms of predic-tive performance along with the increase of TMI. This research can provide support for the study of MLTRP.

The effects of CO₂-water-rock interactions on the mechanical properties of shale are essential for estimating the possibility of sequestrating CO₂ in shale reservoirs. In this study, uniaxial compressive strength (UCS) tests together with an acoustic emission (AE) system and SEM & EDS analysis were performed to investigate the mechanical properties and microstructural changes of black shales with different saturation times (10 days, 20 days and 30 days) in water dissoluted with sub-/super-critical CO₂. According to the experimental results, the values of UCS, Young’s modulus and brittleness index decrease gradually with increasing saturation time in water with sub-/super-critical CO₂. Compared to intact samples, 30-days’ saturation causes reductions of 56.43% in UCS and 54.21% in Young’s modulus for sub-critical saturated samples, and 66.05% in UCS and 56.32% in Young’s modulus for super-critical saturated samples, respectively. The brittleness index also decreases drastically from 84.3% for intact samples to 50.9% for samples saturated in water with sub-critical CO₂, to 47.9% for samples saturated in water with super-critical carbon dioxide (SC-CO₂). SC-CO₂ causes a greater reduction of shale’s mechanical properties. The crack propagation results obtained from the AE system show that longer saturation time produces higher peak cumulative AE energy. SEM images show that many pores occur when shale samples are saturated in water with sub-/super-critical CO₂. The EDS results show that CO₂-water-rock interactions increase the percentages of C and Fe and decrease the percentages of Al and K on the surface of saturated samples when compared to intact samples.

Nanling Mountain region is a typical southern hilly region, which plays an important ecological and environmental protection role in China's overall land protection pattern. Based on the remote sensing image data of Longnan City in Nanling Mountain in 2013, 2018 and 2023, this paper interpreted the land use type and analyzed the land use transfer situation by using Land use transfer flow, and Land use transfer matrix. At the same time, based on the remote sensing Ecological index (RSEI) model, the ecological environment quality of Longnan City from 2013 to 2023 was retrieved. The temporal and spatial response model of ecological environment quality to land use transfer in Longnan City from 2013 to 2023 was discussed based on Spatial autocorrelation and Geographic detector. The results show that from 2013 to 2023, the decrease of forest land (16.23km²) and the increase of construction land (13.25km²) were the main land use transfer in Longnan City. The ecological environment index of Longnan City in 2013, 2018 and 2023 was 0.789, 0.917 and 0.872, respectively, showing a trend of "first rising and then decreasing". The ecological environment quality in the north of Longnan City was significantly lower than that in the south, and the poor ecological quality area appeared in and around the northern main urban area, showing a trend of "inward contraction". Forest land, garden land, grassland, cultivated land and water area have a positive impact on ecological environment quality, while traffic land, construction land and other land have a negative impact on ecological environment quality. The response of ecological environment quality to different land use transfer modes is related to the change of the overall ecological environment quality. The interaction between LUCC and other factors had a great impact on the evolution of ecological environment quality in Longnan City.

Nicaragua is preparing the construction of an interoceanic canal that will be the longest and largest canal on earth. An environmental and social impact assessment has been published in 2014 supporting a general viability of the canal. Nonetheless, several scientist and societal actors raised serious concerns regarding the social, economic and ecological sustainability. Despite an open dispute within the Nicaraguan society, no independent, transparent and scientifically sound assessment has been carried out. Only the environmental and social impact assessment, charged by the canal constructor, has so far been realized. The aim of this study is to contribute to an open scientific debate through an objective and independent quantification of land use and hydrological impacts. This article presents a transparently documented and comprehensible impact assessment investigation of the West Canal Segment of the Nicaragua Canal. Based on publically available data and scientifically sound and recognized methods land use, hydrological (water availability) and socio-economic impacts (streets, population) are described, quantified and compared with official declarations in the impact assessment. While some results support official declarations other do not. The number of affected population and the water use of the Brito Lock resulted much higher in this study, for instance. Hence, society and water availability could be affected much higher than estimated in the impact assessment.

Hydrologic studies on rainfall-runoff have been extensively conducted in many regions around the globe to fulfill various desirable needs with a purpose of effective and proper planning and managing water resources for present and future uses, whereas such study is not well drawn much attention to river catchments of Tonle Sap Lake Basin in Cambodia, which may prevail to water insecurity. The Stung Sreng catchment, which is one among them considered to be a significant basin for water resources management in Cambodia, is remarkably increasing under intolerable pressures in water resources development. This study was to apply HEC-HMS (Hydrological Engineering Center-Hydrological Model System) model to predict streamflow of Stung Sangker catchment, located in Tonlesap Lake Basin in Cambodia. The result showed that the calibration was good at monthly basis. The model performance was given by Nash-Sutcliffe Efficiency criteria followed by 0.44 for daily and 0.71 for monthly basis, respectively. Moreover, the Percent Bias (PBIAS) for daily and monthly simulation was 4.13% and 3.56%, indicating a satisfactory model fit. The HEC-HMS conceptual model can be used to simulate flow of Stung Sangke catchment on a continuous time scale particularly monthly basis. The result also indicated that there was a clear seasonal variation in monthly water availability, especially during both wet and dry season.

The development of accurate dynamic battery pack models for electric vehicles (EVs) is critical for the ongoing electrification of the global automotive vehicle fleet, since these serve as a key element in the energy performance of an EV powertrain system. The Equivalent Circuit Model (ECM) technique at the cell level is commonly employed for this purpose, combining accuracy and efficiency in the representation of battery operation within the broader powertrain system. In this study, a second-order ECM model of a battery cell is being developed using Modelica, an equation-based modeling language. Parameter lookup tables at multiple levels of state of charge (SoC), extracted from Li-ion battery cells with 4 different commonly used cathode materials, have been utilized. This approach allows for a representation of the battery systems that are used in a wide range of commercial EV applications. To verify the model, an integrated EV model is developed and simulation results of the FTP75 driving cycle have been compared against an equivalent application in MATLAB Simulink. The findings demonstrate a close match between the results obtained from both software across different system points. Specifically, the maximum deviation of SoC is limited to 0.08% and the maximum value of relative voltage deviation is 1.4%. The verified model enables the exploration of multiple possible architecture configurations of EV powertrains with Modelica.

Abstract: Due to sever land degradation throughout Ethiopia, the government has been implementing massive soil and water conservation works at the watershed scale since 2010 to conserve soil and water resources. However, most of the rivers in Ethiopia carry huge amount of sediment in rainy season and streams dried up in the dry period. Planned research was conducted on two paired micro-catchments Mt.Yewel with the main objective of evaluating the impact of soil and water conservation measures on base flow modification. Stream flow and rainfall data were collected from 22/11/2020 to 8/11/2022 on both micro-catchments at their outlets and center respectively. Base flow separation was done using Sp. Hydro base flow separation tool and SPSS Ver.21 statistical software was employed for data analysis. Flow duration curve (FDC) for both watersheds were developed. The FDC indicated that the base flow from treated micro-catchment ishigher and sustained in the dry season while it is low and un-sustained in untreated micro-catchment. From statistical analysis, there is a significant difference in base flow enhancement between the treated and untreated micro-catchment (P<0.001). Hence, catchment treatment contributed to improve groundwater recharge and sustain base flow in the dry season by reduce surface runoff during rainy season.

An adequate representation of the water infiltration process in the soil allows improving the efficiency in application and the uniformity in surface irrigation. The Green and Ampt model has shown a good representation of the process, and researchers from the United States Department of Agriculture (USDA) determined the values of their parameters for soils of that country, which are shown in tables or through functional relationships and this information is used as reference in several parts of the world, although there is no certainty that they are representative of the soils in Mexico. In this study, the parameters of the Green & Ampt equation were determined and evaluated in some soils of agricultural importance in Mexico. The parameters were obtained in four ways: one of them applied a methodology adapted from Brooks and Corey to quantify the wetting front capillary pressure head and used an permeameter under constant hydraulic head to determine the saturated hydraulic conductivity, and the other three consisted in taking them from three studies reported by the USDA. The values of the parameters suggested in Mexico drastically underestimated the results with relative errors (RE) in a range of -49.0 to -94.0% and the most representative were those obtained with the methodology proposed in this research with RE of -15.0 to 6.0%.

This paper analyses the application of deep learning techniques for predicting wave overtopping events in port environments using sea state and weather forecasts as inputs. The study was conducted in the outer port of Punta Langosteira, A Coruña, Spain. A video recording infrastructure was installed to monitor overtopping events from 2015 to 2022, identifying 3709 overtopping events. The data collected was merged with actual and predicted data for the sea state and weather conditions during the overtopping events, creating three datasets. We used these datasets to create several machine learning models to predict whether an overtopping event would occur based on sea state and weather conditions. The final models achieved a high accuracy level during the training and testing stages: 0.81, 0.73, and 0.84 average accuracy during training and 0.67, 0.48, and 0.86 average accuracy during testing, respectively. The results of this study have significant implications for port safety and efficiency, as wave overtopping events can cause disruptions and potential damage. Using deep learning techniques for overtopping prediction can help port managers take preventative measures and optimize operations, ultimately improving safety and helping to minimize the economic impact that overtopping events have on the port's activities.

The aim of the study was to test the significance of the EPT index in the water quality assessment of three types of water bodies in hilly and mountainous region of Serbia. The aquatic macroinvertebrate community was dominated by the group of insects, of which 95 taxa represent the EPT group. We compared the obtained values of biological indices used for the assessment of water quality according to the national legislation with the overall status assessment represented by the ecological quality classes (EQC). The results of the Spearman correlation test showed a negative correlation of EQC with the EPT index, BMWP score, H', total number of taxa and number of sensitive taxa, while a positive correlation was observed for the values of SI and Tubificinae %. The values of EQC and biological indices were subjected to principal component analysis (PCA). The results showed that the parameters that contributed most to the differences were the EPT index, the BMWP score and the number of sensitive taxa. The results indicate that the EPT index is an excellent indicator of changes in water quality and an important tool for the ecological categorization of water bodies in mountain regions.

The main contribution of this paper is to develop a graphical tool to evaluate the suitability of a candidate parametric model to fit a data set. The practical motivation is to check the adequacy of the so called SAINT model proposed in Jarner and Kryger (2011). This model has been implemented in practice by an important European pension fund concerned with setting annuity reserves for all current or former employees of Denmark. So, one particular relevant question is whether this mortality model is actually fitting old-age. Our graphical test can be described as follows. First we transform the data by means of the parametric model which is being evaluated. Should the model be correct, the transformed data will be in accordance with an Exponential distribution with rate 1. Then we construct a family of local linear hazard estimates based on the data on the transformed scale. Finally we use the statistical tool SiZer to assess the goodness-of-fit of the Exponential distribution to the data on the transformed scale. If the model is correct the SiZer map should not reveal any significant feature in the family of kernel estimates. Our method allow us to establish a diagnostic regarding the validity of the SAINT model when describing mortality patterns in four different countries.

The sustainable management of water scarcity is a global crucial issue. Germany has es- tablished efficient water management systems, but the agricultural sector still struggles with water scarcity as the demand surpasses the available water supply. The primary aim is to establish a framework for making water accessible for irrigation and additional use on households through the effective utilization of recycled water from wastewater treatment facilities. The research inquiries are focused on evaluating the changes in the agricultural irrigation model in CROPWAT, determining the spatial distribution of zonal severity, estimating the capacity of urban roof catchments, and evaluating the reduction volume of efficient water required from the existing wastewater treatment plant supply. According to the findings, the annual amount of water required for agriculture in the designated study location is approximately 2.9 million m3. Although there is no initial need for irrigation water, yet the demand for irrigation water increases during the development, active growth, and mature stages of maize, winter wheat, and wine grapes, reaching around 189mm, 225mm, and 62mm, respectively. According to our observation, the annual water supply in Weinstadt is around 4 million m3. On the other hand, the amount of water calculated from urban roof rainfall is estimated 0.8 million m3, which is considered valuable from an economic standpoint. This economically efficient volume of water would reduce the current treated water supply passes an opportunity for enhanced agricultural irrigation

Abstract: Severe land degradation is the principal environmental problem in Ethiopian highlands in the form of soil erosion, and soil fertility loss, which is caused by human intervention for food, shelter, and energy demands. Soil erosion contributes to the loss of precious soil and water resources which are the basis of agricultural production and provide numerous other eco-system services. The Ethiopian highlands are one of the most degraded regions in the world. To combat such problems, the government of Ethiopia has been implementing massive soil and water conservation works at the watershed scale since 2010 to conserve soil and water resources. Mount Yewel is one of the highlands in Northeastern Ethiopia where intensive soil and water conserva-tion has been implemented. Despite the massive investment in soil and water conservation measures, most of the rivers in the highlands of Ethiopia carry huge amounts of sediment with high flood risks in the wet season and streams are dried up in the dry period. Nonetheless, the impact of soil and water conservation measures on flood reduction and dry season flow en-hancement has not yet been quantified and evaluated. This research was then conducted on paired micro-catchments of Mount Yewel with the main objective of evaluating the impact of soil and water conservation measures on base flow modification. Stream flow and rainfall data were col-lected from 22/11/2020 to 8/11/2022 on paired micro-catchments of Mount Yewel at their outlets and centers respectively. Base flow separation was done from the stream hydrograph using Sp. Hydro base flow separation tool and SPSS Ver.21 statistical software were employed for data analysis. Flow duration curves (FDC) for both watersheds were developed to compare the stream flow patterns between treated and untreated micro-catchments of Mount Yewel. The FDC indi-cated that the base flow from treated micro-catchment is higher and sustained in the dry season while it is low and unsustained in untreated micro-catchment. From statistical analysis, there is a significant (P

This work investigates the stability conditions for linear systems with time-varying delays via augmented Lyapunov-Krasovskii functional(LKF). Two types of augmented LKFs with cross terms in integral are suggested to improve the stability conditions for interval time-varying linear systems. Through this work, the compositions of the LKFs are considered to enhance the feasible region of stability criterion for linear systems. Mathematical tools such as Wirtinger-based integral inequality(WBII), zero equalities, reciprocally convex approach, and Finsler’s lemma are utilized to solve the problem of stability criteria. Two sufficient conditions are derived to guarantee the asymptotic stability of the systems using linear matrix inequality(LMI). First, asymptotic stability criteria are induced by constructing the new augmented LKFs in Theorem 1. And then simplified LKFs in Corollary 1 are proposed to show the effectiveness of Theorem 1. Second, asymmetric LKFs are shown to reduce the conservatism and the number of decision variables in Theorem 2. Finally, the advantages of the proposed criteria are verified by comparing maximum delay bounds in two examples. Two numerical examples show that the proposed Theorem 1 and 2 obtained less conservative results than existing outcomes. Also, Example 2 shows that the asymmetric LKF methods of Theorem 2 can provide larger delay bounds and fewer decision variables than Theorem 1’s in some specific systems.

This study explores cutting-edge and sustainable green methodologies and technologies for the synthesis of functional nanomaterials, with a specific focus on the removal of water contami-nants and the application of kinetic adsorption models. Our research adopts a conscientious ap-proach to environmental stewardship by synergistically employing eco-friendly silver nanopar-ticles, synthesized using Justicia Spicigera extract as a biogenic reducing agent, in conjunction with Mexican zeolite to enhance contaminant remediation, particularly targeting Cu²⁺ ions. Structural analysis, utilizing X-ray diffraction (XRD) and high-resolution scanning and transmis-sion electron microscopy (TEM and SEM), yields crucial insights into nanocomposite structure and morphology. Rigorous linear and non-linear kinetic models, encompassing pseudo-first order, pseudo-second order, Freundlich, and Langmuir, are employed to elucidate the kinetics and equilibrium behaviors of adsorption. Results underscore the remarkable efficiency of the Zeolite-Ag composite in Cu²⁺ ion removal, surpassing traditional materials, achieving an im-pressive adsorption rate of 98% for Cu. Furthermore, the Zeolite-Ag composite exhibits maxi-mum adsorption times of 480 minutes. In the computational analysis, an initial mechanism for Cu²⁺ adsorption on zeolites is identified. The process involves rapid adsorption onto the surface of the Zeolite-Ag NP composite, followed by a gradual diffusion of ions into the cavities within the zeolite structure. Upon reaching equilibrium, a substantial reduction in copper ion concen-tration in the solution signifies successful removal. This research represents a noteworthy stride in sustainable contaminant removal, aligning with eco-friendly practices and supporting the potential integration of this technology into environmental applications. Consequently, it pre-sents a promising solution for eco-conscious contaminant remediation, emphasizing the utiliza-tion of green methodologies and sustainable technologies in the development of functional na-nomaterials

The collection of photo shoots during the systematic monitoring activities is useful to witness the ecological role of marine phanerogams as hosts for a rich variety of organisms in coastal and transitional waters. Cymodocea nodosa is present in the Taranto seas. In the Mar Piccolo, it reached high covers in short times, up to 100%, due to the bettering of the environmental conditions. The most recent observations showed that it offers welcoming towards several vertebrates and invertebrates, native and non-indigenous, as well as to micro and macroalgae. The NPPR funded activities will make these observations more robust and structural.

Hydrological processes are complex to compute on hilly areas when compared to the plain areas. Most of the hydrological model do not take into account the critical rainfall-runoff generation processes such as subsurface storm flow, saturation excess flow, overland flow, return flow and pipe storage. The simulations of the above processes in the soil matrix requires detailed hillslope hydrological modelling. In present study, a hillslope experimental plot is designed to study the runoff generation processes on the plot scale. The setup is designed keeping in view the natural hillslope conditions prevailing in the north western Himalayas, India where high intensity storm event occurs frequently. Using the experimental data and the developed conceptual model, the overland flow and the subsurface flow through macropore dominated area has been estimated/analyzed on the pixel basis. Over the experimental hillslope plot, a rainfall simulator was installed to generate the rainfall intensity in the range of 15 to 150 mm/hr which represented the dominating rainfall intensity range in the region. Soil moisture sensors were also installed at 100 mm and 300 mm depth at different locations of the plot to observe soil moisture variations. It was found that once the soil is saturated, it remains in the field capacity for next 24-36 hours. Such antecedent moisture conditions are most favorable for the generation of rapid stormflow from hillslopes. Dye infiltration test was also performed on the undisturbed soil column to observe the macropore fraction variability over the vegetated hillslopes. The surface runoff predicted using the developed hillslope hydrological model compared well with the observed surface runoff under high intensity rainfall conditions.

Contamination in coastal regions attributed to fluoride and nitrate cannot be disregarded, given the substantial environmental and public health issues they present worldwide. Maintaining water quality is crucial for environmental well-being. This comprehensive study was performed to assess the spatial as well as indexical water quality, identify contamination sources, and evaluate associated health risks pertaining to nitrate and flouride in AlHassa region, KSA. The physiochemical results revealed a pervasive pollution of the overall groundwater. The dominant water type was Na-Cl, indicating saltwater intrusion and reverse ion exchange impact. Spatiotemporal variations in physicochemical properties suggest diverse hydrochemical mechanisms, with geogenic factors primarily influencing groundwater chemistry. The groundwater pollution index varied between 0.8426 and 4.7172, classifying samples as moderately to very highly polluted. Similarly, the synthetic pollution index (in the range of 0.5021-4.0715) revealed that none of the samples had excellent water quality, with various degrees of pollution categories. Nitrate Health Quotient (HQ) values indicated chronic human health risks ranging from low to severe, with newborns being the most vulnerable. Household use of nitrate-rich groundwater for showering and cleaning did not pose significant health risks. Fluoride HQ decreased with age, and children faced the highest risk of fluorosis. The Hazard Index (HI) yielded moderate to high-risk values. Nitrate risks were 1.21 times higher than fluoride risks, as per average HI assessment. All samples fell into the vulnerable category based on the Total Hazard Index (THI), with 88.89% classified as very high risk. This research provides valuable insights into groundwater quality, guiding water authorities, inhabitants, and researchers in identifying safe water sources and vulnerable human populations. The results highlight the need for appropriate treatment techniques and long-term coastal groundwater management plans.

The aquifer delineation using a hydrogeophysical survey was carried out in De Aar, a small town in the eastern part of the Karoo supergroup, Northern Cape, South Africa. In this re-gion, the current approach for estimating recharge, water allocation plans, and water monitoring does not consider the existence of different types of aquifers. Instead, it assumes there is one aquifer system and therefore the area might have one value of recharge. This study aimed to delineate aquifers into unconfined and confined aquifers for estimating recharge and demonstrate the use of geophysics techniques in delineating aquifer systems. Six VES stations and seven profile lines were measured using a Wenner array configuration and ground magnetotelluric method, respectively. VES data was processed using IPI2win software while electric potential difference curve was in-terpreted together with lithological data. Four significant layers of low (0.9-8.1 Ωm), moderate (22.4-125 Ωm), and high 68-177 Ωm) resistivity values were delineated suggestive of the different lithological formations. The subsurface profile mapping using ground magentotelluric methods did not suggest groundwater accumulations below 50 m, instead supported shallow groundwater potentials boreholes. These results have provided a double layer aquifer system thereby suggesting that recharge estimation need to be carried out in two different aquifer systems to enhance water allocation plans, and water monitoring in groundwater-dependent areas similar to prevailing conditions in the current study area.

The Katerini-Kolindros aquifer system (KKas) is a critical freshwater resource, essential for the local and regional economy. To understand contamination sources, groundwater flow paths, and assess the aquifer's health, an extensive dataset of 751 samples from 113 wells collected between 2010 and 2020 was analyzed using multivariate statistical analysis (MVSA) and hydrogeochemical diagrams. The prevailing water types identified were Ca-HCO₃ and Mg-HCO₃, with mixed water types resulting from various factors affecting groundwater quality. The chemistry of groundwater in the KKas is shown to be affected by ion exchange processes and to a lesser extent by reverse ion exchange processes. No indications of sea-water intrusion have been identified in the water wells monitored. On the other hand, nitrate contamination has been detected in specific water wells spatially associated with urban-type land uses and activities. It is considered that nitrate contamination originates primarily from septic tanks and urban sewage networks or secondarily from fertilization of football pitches, cemeteries or urban waste management practices.

Water quality assessment in pastoral of Tibetan Plateau, which is water sources for about 40% of world's population and the runoff-yield area of Yellow rivers, is very important. In this paper, Xiahe county which belongs to Tibetan Plateau pastoral was investigated. Six parameters(via, chloride, COD, ammonia nitrogen, nitrate, fluoride, sulfate) were selected to assess the water quality and health degree by using fuzzy comprehensive evaluation methods. The hydrochemical type in surface water was of HCO3--Mg2+-Ca2+ type. The cations and anions in surface water were mainly from weathering and dissolution of carbonate rock. Results showed that the water quality in all 69 sampling sites was all of class Ⅰ. The integrated health degree reached more than 0.85 and the health rate were 100%. Although ammonia nitrogen was regarded as the main contamination factor, but it had a little effect on the entire body of water. Overall, the surface water qualities of most samples in Xiahe County was good condition.

A field experiment was conducted for determination of crop coefficient (KC) and water stress coefficient (Ks) for wheat crop under different salinity levels, during 2015-16. Complete randomized block design of five treatments were considered, i.e., 0.51 dS/m (fresh water) as a control treatment and other four saline water treatments (4, 6, 8 and 10 dS/m), for S1, S2, S3 and S4 with three replications. The results revealed that the water consumed by plants during the different crop growth stages follows the order of FW>S1>S2>S3>S4 salinity levels. According to the obtained results, the calculated values of crop coefficients significantly differed from those suggested by FAO No.56 for the crops. The Ks values clearly differ from one stage to another because the salt stress causes both osmotic stress, due to a decrease in the soil water potential, and ionic stress which the average values of water stress coefficient (Ks) follows this order; FW(1.0)=S1(1.0)>S2(1.0)>S3(0.93)>S4(0.82). Overall, it was found the differences are attributed primarily to specific cultivar, the changes in local climatic conditions and seasonal differences in crop growth patterns. Thus, further studies are essential to determine the crop coefficient values under different variables, to make the best management practice (BMP) in agriculture.

: This study examines the prospects of residential water demand management policy regulations in Ethiopia and their implications for sustainable water resource management. This study aims to evaluate the existing policy regulations and analyze their effectiveness in promoting efficient water use and conservation practices in residential areas. By considering the potential challenges and opportunities associated with these regulations, the research provides insights into the future of residential water demand management in Ethiopia and suggests strategies for enhancing sustainable water resource management. Integrated literature and policy document review, alongside observation and interviews, was used to assess the viability of residential water demand management policies. The assessment of current policy regulations for residential water demand management in Ethiopian urban towns has revealed significant shortcomings in promoting water conservation activities. Hence, there is a need for significant improvements in the current water resource policy guidelines, which lack specificity, particularly in residential water demand management conservation strategies. The lack of awareness among residents regarding the importance of conserving their limited water resources is evident. To address these challenges and ensure the sustainability of the water supply, the government and policy developers must engage with various stakeholders, including the community, in the process of revising current policy documents. A more precise and tailored approach is necessary for its effective implementation.

Cambodia is a predominantly agrarian society, with a majority of the population residing in rural areas and relying on agriculture for food and income. The primary sources of food for the Khmer society are rice and fish. However, the country faces vulnerabilities due to climate change, natural disasters, impacts of hydropower and infrastructure development, and land grabs, which disrupt food sources and the livelihoods of local communities. Since 2015, the Royal Government of Cambodia (RGC) has been actively promoting rice production for export, resulting in increased rice farming seasons and annual rice production. Despite these efforts, a significant portion of the population still experiences food insecurity. Therefore, this study aims to explore the reasons why food security issues persist despite the government program to increase rice production. The study involves a review of existing literature and an examination of food security in three provinces in the Cambodian Mekong Delta. It concludes that, on the one hand, the increased rice production has increased food availability, but access to and utilization of food have been challenged by indebtedness, increased cost of production and migration, and on the other hand, the rights to foods have been challenged by land crabs, water conflicts, and lack of sectoral integrations of food systems; and compounded by climate change and environmental degradation, which all contribute to food security.

The widespread proliferation of sensor nodes in the era of Internet of Things (IoT) coupled with increasing usage of wireless spectrums especially the ISM band makes it difficult to deploy real-life IoT. Currently, the cognitive radio technology enables sensor nodes communicate with each other through the licensed spectrum bands as well as the free ISM bands. Cognitive radio networks (CRSNs) are considered as a promising solution to the problem of spectrum under utilization and artificial radio spectrum scarcity. The paradigm of dynamic spectrum access allows secondary users (SUs) to utilize wireless spectrum resources which belong to primary users (PUs) with minimal interference to PUs. Due to the dynamic spectrum availability and quality, routing for SUs in multi-hop CRSNs is a challenge. In this paper, we introduce novel routing metrics that estimate both the future spectrum availability and the average transmission time with the consideration of both the global statistical spectrum usage and local instant spectrum resources. In our novel routing metrics, one retransmission is allowed and considered to reduce the probability of rerouting upon PU's arrival. Then, we propose two routing algorithms for multi-hop CRSNs. Finally, we conduct simulations, whose results show that our proposed algorithms lead to a significant performance improvement over the reference algorithm.

Reducing the carbon footprint of energy production is one of the most pressing challenges facing humanity today. Lignocellulosic biomass residues from fruit production industries show promise as a viable energy source. This paper presents a study of the Italian context concerning the utilization of orchard lignocellulosic residues for energy production as electricity or bioethanol. The potential of various orchard residues was assessed through chemical and physical analysis, and an equivalent electrical energy of about 6441.62 GWh or an amount of 0.48 Mt/y of bioethanol was obtained based on the average annual dry residue mass availability of about 3.04 Mt/y. These data represent the 9.30% of the national electrical energy production from renewable sources, as well as the 6.21% of the Italian demand for gasoline in 2022. Electricity generation from these residues shown its potential as a reliable and sustainable baseload power source, as well as source of renewable transportation fuel. The studied process could be a valuable reference to expand these concepts on global scale to achieve a greener and more sustainable energy future.

The current Global Climate Change, the 2030 Agenda and the Planetary boundaries have driven new development strategies, such as the circular economy, bioeconomy and biorefineries. In this framework, this study analyzes the potential availability and sustainability of the wood supply chain for a small-scale biorefinery aiming at producing 280–300 L of bioethanol per ton dry biomass, consuming 30,000 t of dry biomass per year harvested in a 50 km radius. This wood production goal was assessed from Eucalyptus grandis stands planted for solid wood in northeastern Uruguay. Moreover, to understand the environmental performance of this biomass supply chain, the energy return on investment (EROI), carbon footprint (CF) and potential soil erosion were also assessed. The results showed that the potential wood production would supply an average of 81,800 t of dry mass per year, maintaining the soil erosion below the upper threshold recommended, an EROI of 2.3 and annual CF of 1.22 kg CO_2-eq m^–3 (2.6 g CO_2-eq MJ^–1). Combined with the environmental performance of the bioethanol biorefinery facility, these results would show acceptable values of sustainability according to EU Directive 2009/28/ec because the bioethanol CF becomes 1.7% of this petrol’s CF.