Globally, groundwater is the largest distributed storage of freshwater and plays an important role in an ecosystem’s sustainability in addition to aiding human adaptation to both climatic change and variability. However, groundwater resources are dynamic and often change as a result of land usage, abstraction, as well as variation in climate. To solve these challenges, many conventional solutions, such as certain numerical techniques, have been proffered for groundwater modelling. The global evolution of the Internet of Things (IoT) has enhanced the culture of data gathering for the management of groundwater resources. In addition, efficient data-driven groundwater resource management relies hugely on information relating to changes in groundwater resources as well as their availability. At the moment, some studies in the literature reveal that groundwater managers lack an efficient and real-time groundwater management system that is needed to gather the required data. Additionally, the literature reveals that the existing methods of collecting data lack the required efficiency to meet computational model requirements and meet management objectives. Unlike previous surveys, which solely focussed on particular groundwater issues related to simulation and optimisation management methods, this paper seeks to highlight the current groundwater management models as well as the IoT contributions.

Estimating parameters for multiple datasets can be time consuming, especially when the number of datasets is large. One solution is to sample from multiple datasets simultaneously using Bayesian methods such as adaptive multiple importance sampling (AMIS). Here we use the AMIS approach to fit a von Misses distribution to multiple datasets for wind trajectories derived from a Lagrangian Particle Dispersion Model driven from a 3D meteorological data. The primary objective is to characterise the uncertainties in wind trajectories in a form that can be used as inputs for predictive models of wind-dispersed insect pests and pathogens of agricultural crops for use in evaluating risk and in planning mitigation actions. Our results show that AMIS can significantly improve the efficiency of parameter inference for multiple datasets.

This study presents the results of a research project financed by the Lazio Regional Government. The research focused on defining an integrated model of recent alluvial deposits in the Tiber River. To achieve this objective, geological boreholes were made to monitor the aquifer and in situ and laboratory tests carried out. The data obtained was used to detail stratigraphic aspects and improve the comprehension of water circulation beneath the recent alluvial deposits of the Tiber River in the urban area of Rome, between the Ponte Milvio bridge and the Tiber Island. The stratigraphic intervals recognised in the boreholes were parameterised based on their litho-technical characteristics. The new data acquired, and integrated with existing data in the CNR IGAG database, made it possible to produce a three-dimensional model of the lithologies in the study area.The model of the subsoil, simplified for applied reasons, was described in hy-drostratigraphic terms: three different lithotypes were subjected to piezometric levels monitor-ing. Finally, the research generated a numerical hydrological level in a stationary regime. In general, this study demonstrates how a numerical hydrogeological model calibrated by piezo-metric monitoring data can support the construction of a geological model, discarding or con-firming certain hypotheses and suggesting other means of reconstructing sedimentary bodies.

Groundwater is a vital resource for human welfare. However, due to various factors, groundwater pollution is one of the main environmental concerns facing. Yet, it is challenging to simulate groundwater quality dynamics due to the insufficient representation of nutrient percolation processes in the soil and Water Assessment Tool model. The objectives of this study were extending the SWAT module to predict groundwater quality. The results proved a linear relationship between observed and calculated groundwater quality considering No3 and TDS with R2, NSE and PBIAS values in the satisfied ranges, albeit underestimation and overestimation were observed due to limited data availability. These results highlight that nitrate and TDS concentrations and variability in groundwater may used as a tool in surface water quality that have to be assumed for designing adaptive management scenarios. Hence, extended SWAT model could be a powerful tool for future regional to global scale modelling of nutrient loads supporting effective surface and groundwater management.

Despite being stored at 113 K and atmospheric pressure, LNG cold potential is not exploited to reduce green ships’ energy needs. An innovative system based on three Organic Ranking Cycles integrated into the regasification equipment is proposed to produce additional power and recover cooling energy from condensers. A first-law analysis identified ethylene and ethane as suitable working fluids for the first and the second ORC making available freshwater and ice. Propane, ammonia and propylene could be arbitrarily employed in the third ORC for air-conditioning. An environmental analysis that combines exergy efficiency, ecological indices and hazard aspects for marine environment and ship’s passengers, indicated propylene as safer and more environmentally friendly. The exergy analysis confirms more than 20% of the LNG potential can be recovered from every cycle to produce a net clean power of 76 kW, whereas 270 kW can be saved by recovering condensers' cooling power to satisfy some ship needs. Assuming the sailing mode, a limitation of 162 kg in LNG consumptions was determined, avoiding the emission of 1584 kg of CO2 per day. Marine thermal pollution is reduced by 3.5 times by recovering the working fluids' condensation heat for the LNG pre-heating.

The strong competition in the automotive industry has required manufacturers to implement lean production, both with methods and techniques specific to Industry 4.0. At the same time, universities must provide graduates with specific skills for applying these new production methods and techniques. In this context, a Lean Learning Factory was developed in the Pitesti University Center, which allows students to learn, experiment, and research, in an environment similar to that of enterprises, the new Lean Manufacturing methods and techniques, and Industry 4.0. The research presented in this study had as its objective identifying the minimum number of repetitions necessary to train operators who serve two differently organized workstations, one classic, the other including digital techniques, but on which the same assembly operation is performed. Several indicators were considered in the analysis, such as the number of errors, the number of stops, the effective duration of the work cycle, and the percentage ratio between the standard duration of cyclical activities and the effective duration of the work cycle. The evolution of these indicators was mathematically modelled by regression functions, using the least squares method. The obtained results also highlight the usefulness of applying the DOJO method as a Lean manufacturing-specific learning technique and the efficiency of implementing digital techniques in work organization.

This paper concerns about a stepwise modelling procedure for groundwater flow simulation in a complex carbonate, folded and faulted, multilayer aquifer, in the Apennine chain in Central Ita-ly, which constitutes a source of good quality water for human consumption. A perennial river acts as the main natural drain for groundwater while sustaining valuable water related ecosys-tems. The spatial distribution of recharge was estimated using the Thornthwaite-Mather method on 60 years of climate data. The system was conceptualized as three main aquifers separated by two locally discontinuous aquitards. Three numerical models were implemented by gradually adding complexity to the model grid: single layer (2D), three layers (Quasi-3D), and five layers (Fully-3D), using an equivalent porous medium approach, in order to find the best solution with a parsimonious model setting. To overcome dry-cell problems in the Fully-3D model, the New-ton-Raphson formulation for MODFLOW-2005 was invoked. Calibration results show that a Fully-3D model was required to match the observed distribution of aquifer outflow to the river baseflow. The numerical model demonstrated the major impact of folded and faulted geological structures on controlling the flow dynamics in terms of flow direction, water heads and spatial distribution of the outflows to the river and springs.

The expansion of renewable energies is progressing strongly. The influence on the power supply networks by the volatility of the infeed must be met with new concepts. In this paper we investigate the possibilities of integrating microgrids as a cooperating unit in the power supply network to support further expansion of RES power plants. In this paper a differentiation of microgrids from similar network structures is established, a classification of proposed groups is made. Then, after the description of simulation of components in a microgrid, with practical advice, an example model is shown, which aids the dimensioning of the components within a microgrid to achieve a specified goal.

When wildlife and motor vehicles collide, the result for the animals is often death (roadkill). A commercial roadkill Virtual Fence (VF) mitigation device (iPTE Traffic Solutions) was used in a field trial to test its effectiveness along a 4.9-km segment of road on Bruny Island, Tasmania. A total of 585 days of monitoring of roadkill by species was conducted, with six sections alternatively switched on or off, according to a variation of a Crossover and Multiple Before-After-Control-Impact (MBACI) experimental designs that divided monitoring into “off-on” then “on-off” blocks of periods with each “on” period followed by a 16 d “wash-out” period. For the six sections over the four periods that exclude wash-outs, the 24 aggregated values of daily counts of roadkill of Tasmanian pademelons (Thylogale billardierii), that gave a total count of 222, were modelled. Other species were killed in insufficient numbers for analysis to be informative. The statistical analysis exploited the MBACI design to estimate the VF effect using a log-odds ratio parameter (LORP) while accounting for local spatio-temporal effects. Both versions of the analysis, either averaging over the three spatial replicates (paired sections) or two temporal replicates (blocks) gave no statistically significant effect of the VF judged as a LORP estimate not sufficiently below zero. Corresponding percentage reduction estimates of 9% and 16% were derived from the LORP estimates and given parameter uncertainty estimates the power to detect as significant a LORP corresponding to a 50% reduction in rate were 0.5 and 0.6, respectively. This study confirms results from a similar field trial carried out in 2018 also in southern Tasmania and adds to the evidence that this VF is likely to give if anything only a minor reduction in roadkill for a commonly killed species for which researchers have the best chance of detecting any practically useful reduction.

Performing optimisation and scale-up studies of crystallisation systems requires accurate and computationally efficient mathematical models. The assumption of the ideal mixing conditions in batch reactors typically produce inaccurate results while the computational expense of CFD models is still prohibitively high. Therefore, in this work, a new intermediary approach is proposed that takes into account the non-ideal mixing conditions in the reactor and requires less computational resources than full CFD simulations. Starting with the Danckwerts concept of the intensity of segregation, an analogy between its application to chemical reactions and the kinetics of the crystallisation phenomena (such as nucleation and growth) has been made. As a result, the modified kinetics expressions have been derived which incorporate the effect of non-idealities present in stirred reactors. This way, based on the experimental measurements of the mixing time using the Laser Induced Fluorescence (LIF) technique, computationally more efficient mathematical models can be developed in two ways: (1) the accurate semi-empirical correlations are available for standard mixing configurations with the most often used types of impellers, (2) CFD simulations can be utilised for estimation of the mixing time; in this case it is necessary to simulate only the mixing process. The benefits offered by the LIF experimental technique have been demonstrated and some frequent problems in its application analysed. The mixing time results for configurations with and without baffles for three types of impellers and four different rotational speeds have been presented. The false shorter mixing times in the non-baffled configurations have been observed and this phenomena explained by the existence of two segregated zones in the reactor and confirmed by additional experiments. The precise measurements in these cases have been shown as difficult using the LIF technique, particularly for higher rpms. The experimental data has been compared to the preliminary simulation results obtained from the Smoothed Particle Hydrodynamics method and the standard k-ε turbulence model with the modest success. The shortcomings of the SPH model have been recognized and the directions for the future work discussed.

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.

Energy consumption modelling is of critical importance for improving energy efficiency in the drive towards sustainable manufacturing. Modern manufacturing processes and machine tools are very complex as they involve interplay of several advanced technologies. Therefore, energy modelling of modern machine tools is a complex multi-disciplinary task. This paper proposes a systematic and practical framework to choose the appropriate modelling approach for a given industrial problem. The framework was validated by applying it to diverse industrial scenarios.

Schistosomiasis, acquired by skin-penetrating cercariae of dioecious digenean schistosomes during freshwater contact, afflicts nearly 260 and 440 million people with active infections and residual morbidity, respectively; about 10 million women at reproductive age contract schistosomiasis during gestation every year. Acute schistosomiasis is characterized by pre-patent pro-inflammatory CD4+ T-helper 1 or CD4+ Th1/T-helper 17 reactivity against immature schistosomulae. Chronic schistosomiasis is dominated by post-patent anti-inflammatory CD4+ T-helper 2 reactivity against ova epitopes; flukes co-exist in immunocompetent definitive hosts as they are capable of evading their defense mechanisms. Preventive measures should be complemented by vaccination, inducing long-term protection against transmission, infection, and disease recurrence, given the latest advancements in schistosomal vaccines. Transmission models incorporating vaccination available in PubMed, Embase and Web of Science up to December 31, 2023 are presented. Besides conceptual model differences, predictions meant to guide decision- and policymaking reveal continued worm harboring facilitating transmission besides residual infections, and increased susceptibility to re-infection and rebound morbidity, both shifted to later life stages following the intervention. Consequently, a vaccination schedule is pivotal considering the optimal age for initial immunization, i.e., pre-schoolchildren or schoolchildren, in a cohort-based or population-based manner while incorporating potential non-adherers promoting ongoing transmission; longevity over magnitude of vaccine protection to antigenic schistosomal moieties is crucial including accounting for existing pre-acquired immunity from natural exposure, in utero priming besides herd immunity, and induced by chemotherapy. Combining as one multi-component approach long-term effects of vaccination with short-term effects of chemotherapy as regular repeated vaccine-linked therapy in contrast to a single-component intervention seems most promising for achieving WHO’s endpoints of transmission elimination and morbidity control.

Water footprint has been widely used to illustrate the consumption of water in many situations; for instance, in products, processes or regions of interest. In this work, we analyzed – using a sensitivity analysis approach – the effect of some variables in the calculation of the water footprint in the viticulture in Brazilian Serra Gaúcha (the major producing region of Brazilian Wine).The classical Penman-Monteith model for evapotransporation was considered, with uncertainties in some parameters (dead mulch covering fraction in the vineyard, maximum temperatures for some months, altitudes and latitudes of the site). The sensitivity analysis was conducted using the SAFE toolbox under Octave framework. The results indicated that the the portion of the water footprint corresponding to the evapotranspiration is more sensitive to the values of mulch covering fraction and the altitude of the site in comparison with the latitude and the maximum temperatures.

The water quality index (WQI) and irrigational index for groundwater were studied in the northeastern section of the Manipur Valley in northeast India. Water samples were collected in 2022 during the pre-monsoon season. To compute the water quality index for drinking water, the basic chemical parameters of total hardness, pH, electrical conductivity, total dissolved solids, Ca2+, Na+, Fe, Mg2+, Mn, Cl-, and HCO3, were used. The assessment of bacteriological quality is also done, which is crucial for overall water quality evaluation, alongside physical and chemical analyze. For determining irrigation suitability, irrigational indices such as sodium absorption ratio, sodium percentage, and magnesium hazard were calculated. WQI, %Na+, SAR, magnesium hazard, permeability Index and total hardness indicate that most water samples are harmless for irrigation and drinking purpose. They have affirmative relationships indicating that these characteristics are interdependent. Approximately 25% of the Piedmont zone groundwater is found to be unfit for agricultural and drinking usage. The encrustation of gypsum, halite, and evaporation into the Disang shares accelerate the dissolution of ions in Piedmont water, resulting in quality degradation. According to Gibbs plots, Durov Scatter Plot, and Hill Piper Trilinear Diagram of water dominated the rock-weathering process, while hydro chemical facies progressed from the beginning to the intermediate stage of Chadha's graphical representation illustrates the progression of hydro chemical processes in surface water. Therefore, proper integrated water resource management and development are required for effective water resource utilization, particularly around the Piedmont zone. To prevent a water crisis, groundwater resources must be managed sustainably. The current study also concentrated on a bibliometric examination of groundwater management and access to gauge the state of the field.

Packaged water consumption has grown rapidly in urban areas of many low and middle income countries, but particularly in Ghana. However, the sources of water used by this growing packaged water industry and its implications for water resource management and transport-related environmental impacts have not been described. This study aimed to assess the spatial distribution of regulated packaged water production in Ghana, both in relation to demand and for natural mineral water, to hydrogeological characteristics. 764 addresses for premises licenced to produce packaged water from 2009-2015 were mapped and compared to regional sachet water consumption and beverage import/export data examined. We find evidence to suggest packaged water is transported shorter distances in Ghana than in developed countries. For natural mineral waters, producers should be able to address the most widespread water quality hazards (including high salinity, iron and nitrates) in aquifers used for production through reverse osmosis treatment. The study suggests there is scope to integrate beverage product and groundwater regulatory databases to support groundwater management.

Reservoirs created by damming rivers significantly modify the environment and problems may arise: the storage of nutrients and organic matter in reservoirs often leads to decreased water quality due to eutrophication. Reservoirs built on lowland rivers are exposed to significant nutrient loads, often leading to eutrophication. In this article, the Sulejów Reservoir, in Central Poland, was the subject of the research, which focused on the use of Sentinel-2 remote sensing data to detect phytoplankton blooms, and on understanding the pattern of wind-driven surface currents using the CCHE2D model (a depth-averaged hydrodynamic model). The calculation of the total phosphorus load has shown that the reservoir mainly acts as nutrient storage. Still, during the low flow and intensive phytoplankton bloom, it can be a source of nutrients. The distribution of phytoplankton bloom on the Sulejów Reservoir was documented using eight Sentinel-2 satellite images from the vegetation season of 2020 and the Normalized Difference Chlorophyll Index (NDCl). Coupling remote sensing data and numerical modelling helps to interpret the hydrodynamic model results and understand nutrients and sediment dynamics within the reservoir. Hydrodynamic modelling combined with remote sensing data can be a valuable tool for selecting appropriate locations for water quality measurements at monitoring stations.

The partial discharge (PD) event in high voltage insulation releases energy, exerts mechanical pressure, and generates elastic waves. Detecting and locating these PD events through short-duration acoustic pulses is well-established, particularly in gas-insulated systems and oil-insulated transformers. However, its full potential remains untapped in solid insulation systems, where the propagation capability of acoustic pulse and the acoustic reflections pose fundamental challenges to the Acoustic Emission (AE) detection technique. This study investigates the influence of reflections and multiple paths on the propagating acoustic pulse in polymeric insulating materials using a finite element method (FEM) in COMSOL. It was observed that the reflections from the boundary influence the propagating pulse's shape, peak magnitude, and arrival time. An analytical MATLAB model further quantifies the impact of multiple propagation paths on the shape, magnitude, and arrival time of the pulse travelling in a cylinder. Additionally, a Perfect Matched Layer (PML) was implemented in the COMSOL model to eliminate reflections from the boundary, and it revealed that the acoustic pulse magnitude decreases with distance following the inverse square law. In essence, the models aid in measuring how reflections contribute to the observed signals, facilitating the precise identification of the source of the PD event in the tested system.

We are witnessing a progressive divestment of some institutions with strong traditions and skills in physical modelling and their consequent impoverishment, to the detriment of numerical modelling. For many reasons, the economic imperatives and the exponential growth of computational means and numerical methods should certainly not be excluded. In this work, we aimed to highlight the new requirements of the recent sophisticated developments in physical modelling, precisely due to the new needs imposed on them by mathematical and numerical modelling and the growing risks in civil construction works. In this context, reflections are reported, justified by scientific and real-world examples, on the need for maintenance and reinforcement of investments in physical modelling, both to support the scientific community and to design buildings of significant economic, social and environmental impact.

This paper seeks to model the crack propagation in of AAs (aluminum-alloys) 2524-T3 and 7050-T7452 subjected to fatigue loading at low temperature. Fatigue crack growth tests were performed on AAs 2524-T3 and 7050-T7452 subjected to constant-amplitude and actual random-spectra loading histories at room temperature of about 25 °C and at cryogenic temperature of -70 °C, respectively, to determine their crack growth properties and residual lives. The interaction mechanisms between cryogenic temperature and the fatigue load were deduced on the basis of the results of fractographic analysis. Temperature-dependent residual lives under actual random-spectrum load history were modeled based on a modified accumulation damage rule by accounting for the load interaction. Good correlation was achieved between the predictions and actual experiments, demonstrating the practical and effective use of the proposed method.

.(1) Background: Groundwater resources management in dry lands, characterized by climate var-iability and population growth, is difficult. Exploration and exploitation of groundwater, due to inadequate surface water is very costly. The present study employed Analytic Hierarchy Process (AHP) and GIS to identify Ground-Water Potential (GWP) areas in a semi-arid region of Nigeria; (2) Methods: Land-use-land-cover, drainage density, slope, rainfall, static water level, soil media, vadose media and aquifer media were selected for GWP analysis. Parameters weights were de-termined using AHP and ranked based on their contribution to GWP by experts. The parameters were then integrated using weighted overlay tool in ArcGIS 10.5 to produce GWP map of the study area. Boreholes yield data from 245 wells were collected to determine the model accuracy and model validation; (3) Results: Results classified the study area into very high GWP (1.9%), high GWP (8.8%), moderate GWP (62%), low GWP (20.70%) and very low GWP (6.6%). Validation of the AHP model with boreholes yield data shows a correlation coefficient of 71.3% giving a good prediction; (4) Conclusions: AHP and GIS can be used to successfully map GWP areas which could serve as an exploration guide for sustainable management of groundwater resources in semi-arid areas.

Even though groundwater-based irrigation has increased agricultural productivity and economic activity in the United States (US), the current rate of groundwater withdrawals from major aquifers could significantly affect the sustainability of agricultural production systems in the near future. In the major agricultural regions, producers are now facing challenges to irrigate to meet full crop water needs. There is an increasing need to strategize irrigation management under various climatic and environmental conditions to optimize water use in agriculture while optimizing crop yields. This study reviews some of the major challenges facing irrigated agriculture in the US and the potential measures to ensure the sustainability of groundwater-based irrigation. Identified challenges included diminishing quantity and quality of groundwater resources, frequent droughts, low adoption rates of precision irrigation technologies, and rising energy requirements for irrigation abstractions. Irrigation efficiency improvements, shifting to high water use efficiency crops, wastewater reuse, groundwater monitoring, availing incentives, and policy changes, were identified as promising water management strategies to ensure irrigation sustainability. The success of these strategies will depend on the uptake and adoption by the producers in the affected agricultural regions.

The Earth's fresh water resources predominantly is groundwater that is pumped out due to rapid urbanization and aggravated by climate change. Groundwater modeling is a crucial tool for understanding aquifer systems, employing 1D, 2D, and 3D numerical models with distinct applications. One-dimensional models focus on vertical dynamics, examining aquifer properties and simulating vertical contaminant transport. Two-dimensional models extend to regional scales, considering horizontal variations and assessing groundwater-surface water interactions, making them valuable for watershed-scale studies. Three-dimensional models provide a comprehensive representation of hydrogeological systems, capturing intricate flow patterns and aiding site-specific assessments. Comparative analysis reveals model strengths and limitations, emphasizing the importance of calibration for reliable results. Case studies showcase practical applications, such as 1D models in flooding analysis and 2D models for simulating debris flows. Three-dimensional modeling proves essential for understanding complex river-aquifer exchange fluxes. Future directions call for a global groundwater platform to address data variability and technical challenges. Despite substantial investments required, the anticipated returns in scientific advancements, societal benefits, and economic gains are expected to outweigh the initial costs. This review aims in highlighting the significance of advancing all three-dimension groundwater modeling for sustainable water resource management and environmental protection.

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.

With the rapid development of urbanization, the chemical evolution of groundwater is significantly affected by human activities. However, the driving mechanisms of groundwater chemical evolution at different stages of urbanization remain unclear, severely impacting the implementation of groundwater protection. This study investigated the driving mechanisms of groundwater chemical evolution based on the long-term series (from 1985 to 2015) of hydrochemical data from 19 groundwater monitoring sites in rapidly urbanizing areas (Shijiazhuang, Hebei Province, China). The results show that the concentrations of various chemical components in groundwater gradually increase with the acceleration of urbanization process, especially NO3-, which has increased from 13.7 mg/L in the primary stage of urbanization (PSU) to 65.1mg/L in the advanced stage of urbanization (ASU), exceeding the WHO drinking water standard (50mg/L), indicating that the groundwater chemistry has been significantly affected by human activities. It is interesting to find that the main hydrochemical types have changed from HCO3•SO4-Ca•Mg type water in the PSU to SO4•HCO3-Ca•Mg type water in the ASU. It is worth noting that there were obvious differences in driving factors of groundwater chemical evolution at different urbanization stages. In the PSU, the driving factors of groundwater chemical evolution were carbonate and rock salt dissolution, cation exchange, and industrial activities. However, in the intermediate stage and advanced stage, the driving factors of groundwater chemical evolution were changed to carbonate and gypsum dissolution, groundwater over-exploitation, agricultural fertilization, and domestic sewage. Based on the above conclusions, it is suggested that future groundwater management should control the amount of agricultural fertilizers, apply scientific fertilization, and prohibit the discharge of various types of non-compliant sewage, while strengthening the supervision of groundwater extraction to reduce the impact of urbanization development on the groundwater chemical evolution process.

This paper is motivated by spatio-temporal pattern in the occurrence of Leishmaniasis in Afghanistan and the relatively high number of zero counts. We hold the view that correlations that arise from spatial and temporal sources are inherently distinct. Our method decouples these two sources of correlations, there are at least two advantages in taking this approach. First, it circumvents the need to inverting a large correlation matrix, which is a commonly encountered problem in spatio-temporal analyses. Second, it simplifies the modelling of complex relationships such as anisotropy, which would have been extremely difficult or impossible if spatio-temporal correlations were simultaneously considered. We identify three challenges in the modelling of a spatio-temporal process: (1) accommodation of covariances that arise from spatial and temporal sources; (2) choosing the correct covariance structure and (3) extending to situations where a covariance is not the natural measure of association. Moreover, because the data covers a period that overlaps with the US invasion of Afghanistan, the high number of zero counts may be the result of no disease incidence or lapse of data collection. To resolve this issue, a model truncated at zero built on a foundation of the generalized estimating equations was proposed.

The second article in the series presents the application of the Smoothed Particle Hydrodynamics (SPH) method to modelling of batch crystallisation in stirred tanks. A methodology to integrate the population balance equations (PBE) in parallel and independently from the Navier-Stokes equations is demonstrated. The benefits of the proposed methodology in terms of computational requirements, accuracy and availability of the crystal size distribution are discussed. The specific formulation of the SPH equations where the resulting system of ordinary differential equations is solved using the weighted contributions rather than numerically by solving a linear system of equations allows for massive parallelisation and a very loose coupling of the population balance and the fluid dynamics. It has been demonstrated, that the population balance equations can be solved on a Shared Memory Architecture (SMA) system using the OpenMP interface while the fluid dynamics equations being computed independently on a General Purpose Graphics Processing Unit (GPGPU) using the NVidia CUDA technology. This way, a significant portion of the computational overhead due to the large number of additional transport equations resulting from the discretisation of the population balance was removed: the SPH simulation coupled with 200 population balance equations was only 40% slower compared to SPH-only simulation. Two methods for the solution of population balance equations that preserve full crystal size distribution were implemented: discretised population balance (DPB) and method of characteristics (MOCH). The DPB equations are solved using the high-resolution finite-volume method with flux limiter and the effect of a large number of different flux limiters have been investigated. Both methods were validated using the case studies from the literature where an analytical solution can be derived. The developed models were applied to a numerical solution of coupled computational fluid dynamics and population balance equations to model a batch crystallization process. The effect of the hydrodynamics on the local temperature/supersaturation and the resulting crystal size distribution was captured and compared to the ideal mixing case. The simulation results from the DPB and MOCH methods were compared in terms of computational requirements and accuracy and MOCH selected as computationally more efficient and accurate.

(max 200 words): The contamination of groundwater is a serious concern for ecosystems and human health. In this regard, biochar represents a promising low-cost and sustainable material for in-situ groundwater remediation. Herein, biochar waste of biomass energy production process derived from pine wood gasification at 950°C was used as active carbonaceous material in combination with different biopolymers: chitosan (CS), alginate (ALG), potato starch (PST), and carboxymethylcellulose (CMC) to produce BC@biopolymer composite materials. Different concentrations of biochar (0.3–1.0 g·L-1) and biopolymers (0.2–20.0 g·L-1) were tested and blending mode was used as simple and straightforward strategy to obtain BC composites. Scanning electron microscopy (FE-SEM), UV-Visible, infrared (FT-IR) spectroscopy, specific surface area (BET method), pore volume, and pore size distribution (textural parameters), dynamic light scattering (DLS), and ζ-potential were used to investigate the composite chemical structure, stability, and to assess the interaction among counterparts. On optimized formulations, breakthrough tests and batch adsorption isotherms on trichloroethylene (TCE) as a model contaminant were performed to evaluate the capability of composites to be delivered through a porous medium determining the transport properties, (hydrodynamic dispersion retention percentage, and adsorption capacity). This biopolymer-modified biochar holds significant promise as a sustainable and effective solution to address various groundwater pollution challenges.

Problem solving is one of the most important components of the human cognition that affects for ages the progress of the human society. Mathematical modelling is a special type of problem solving concerning problems related to science or everyday life situations. The present study is a review of the author’s earlier works on problem solving and mathematical modelling from the scope of Education. Its real goal is that it presents in a systematic way and in a few pages only the results of many years research on the subject. This helps the reader to get a comprehensive idea about a very important topic belonging to the core of Mathematics Education, which is very useful to those wanting to study deeper the subject and get directions for further research in the area.

In the present work, a predictive modelling and optimization with the adaptive network based fuzzy inference system(ANFIS) modelling of mechanical properties of laser-coated NB/SiC/Ni welds was studied based on Taguchi design by laser cladding. An ANFIS model based on a Sugeno type fuzzy inference system was developed for predicting the hardness properties of SiC/BN/Ni welds by laser cladding with experimental data required for network training and prediction. Based on analysis of variance, three important factors were taken as inputs for the fuzzy logic inferences, while the hardness properties was taken as the output of the ANFIS. The microstructure of welds were analysed using scanning electron microscopy with an energy dispersive X-Ray spectrometer. Highly developed leaf-like dendrites and eutectic crystals were found in some areas of the melting zone for the BN/SiC/Ni weld, which was significantly hardened. The ANFIS model based on Taguchi's design provides a better pattern of response because the predicted and experimental values were highly similar. As a result, a satisfactory result was achieved between the predicted and experimental values of hardness in laser-coated NB/SiC/Ni welds, whereby the success and validity of the method was verified.

226Ra and 228Ra are typically monitored for groundwater and surface water compliance at legacy U mining and milling sites. Groundwater monitoring results for combined Ra (226Ra+228Ra) reported by the existing contract laboratory at a former U mine and mill Site (Wyoming, USA) have been highly variable and with increasing trends at the Site compliance and background wells since the method was changed in 2005. Sample reanalysis has indicated poor reproducibility and significant analytical error in 228Ra measurements. An interlaboratory comparison was conducted to evaluate the potential causes of the high variability and analytical error. Two different methods were used for 226Ra (M903.0 and M903.1) and 228Ra (M904.0 and Ra-05). 226Ra results were less variable compared to 228Ra, and 228Ra data from the existing laboratory were qualified as estimated with high bias due to detection of 228Ra in the field blank. Compliance with the 226Ra+228Ra groundwater standard was either met or not met, depending on which laboratory conducted the analyses. Specific laboratory techniques, rather than the analytical method, are contributing to elevated 228Ra values being reported. It was recommended that samples whose 226Ra+228Ra results exceed the Site standard in the future be reanalyzed by the existing laboratory with a sample split also being sent to an outside laboratory for confirmatory analysis.

Traumatic Brain Injury represents a significant public health concern due to its role in traumatic death and disability, often caused by head impacts or rapid accelerations. Despite advancements in Finite Element Head Models, existing models primarily represent adult males, neglecting anatomical and physiological differences between genders and age groups. Additionally, the mechanistic roles of specific intracranial tissues, such as the dura mater, have conventionally been overlooked. To better understand the mechanical behavior of the brain and its injured regions in the context of TBI, including the dura mater, this study proposes the development of a Female Finite Element Head Model. This model, representative of a middle-aged female subject, was developed using medical image-derived geometry and finite element modeling techniques. The validation results demonstrate a similarity between the numerical displacement curves and those obtained experimentally. In the model with dura mater, the numerical results show analogous behavior to the experimental results, despite minimal variations in the amplitude of the curves. These advancements highlight the significance of including the dura mater in biomechanical brain modeling. Incorporating the dura mater in Finite Element Head Models produces more realistic results than models without it. This emphasizes the importance of enhancing biomechanical models to better represent anatomical complexity.

This work (in two parts) will review the recently developed predictive modeling methodology called “4th-BERRU-PM” and its applicability to energy systems as exemplified by an illustrative application to the Polyethylene-Reflected Plutonium (acronym: PERP) OECD/NEA reactor physics benchmark. The acronym 4th-BERRU-PM designates the “Fourth-Order Best-Estimate Results with Reduced Uncertainties Predictive Modeling” methodology, which yields best-estimate results with reduced uncertainties for the first fourth-order moments (mean values, covariance, skewness, and kurtosis) of the optimally predicted posterior distribution of model results and calibrated model parameters. The 4th-BERRU-PM uses the Maximum Entropy (MaxEnt) principle to incorporate fourth-order experimental and computational information, including fourth (and higher) order sensitivities of computed model responses to model parameters, thus incorporating, as particular cases, the results previously predicted by the second-order predictive modeling methodology 2nd-BERRU-PM, and vastly generalizing the results produced by extant data assimilation and data adjustment procedures. The 4th-BERRU-PM methodology encompasses the scopes of high-order sensitivity analysis (SA), uncertainty quantification (UQ), data assimilation (DA) and model calibration (MC). The application of the 4th-BERRU-PM methodology to energy systems is illustrated by means of the above-mentioned OECD/NEA reactor physics benchmark, which is modeled using the neutron transport Boltzmann equation involving 21976 imprecisely known parameters, the solution of which is representative of “large-scale computations.” The model result (“response”) of interest is the leakage of neutrons through the outer surface of this spherical benchmark, which can be computed numerically and measured experimentally. Part 1 of this work illustrates the impact of high-order sensitivities, in conjunction with parameter standard deviations of various magnitudes, on the determination of the expected value and variance of the computed response in terms of the first four moments of the distribution of the uncertain model parameters. Part 2 of this work will illustrate the capabilities of the 4th-BERRU-PM methodology for combining computational and experimental information, up to and including forth-order sensitivities and distributional moments, for producing best-estimate values for the predicted responses and model parameters while reducing their accompanying uncertainties.

Earthquakes often entail alterations in the groundwater flow regime, in the phreatic level, in the surge and loss of springs, and discharge in brooks and springs. As for the latter, there are diverse feasible mechanisms, so there is a variety of theoretical approaches to elucidate the post-earthquake effects on spring discharge. This study adopts a conceptual approach, primarily presenting various methods for estimating water released by earthquakes by calculating discharge surpluses in springs. This study delves into refined techniques rooted in groundwater hydraulics, displaying applications of analytical and simulation methodologies to quantify seismic-induced groundwater discharge in springs. Investigating springs as natural indicators, this research applies mathematical precipitation-runoff models, specifically the CREC model, for simulating hydrographs in post-earthquake scenarios. We apply analytical procedures or mathematical simulation techniques employed in groundwater hydraulics for natural aquifer recharge calculations. Firstly, we briefly describe the methods based on the analysis of depletion curves of hydrographs in spring discharge. Additionally, certain mathematical rainfall-runoff models utilized in simulating hydrographs of karstic springs, along with derived analytical approximations, are adapted for this scenario. These hydraulic calculations involve the depletion coefficient and hydrodynamic volumes of aquifers, parameters that reveal certain aspects of the relation between groundwater and earthquakes, such as: a) Acknowledging faults as the primary geological structures in transmitting pore pressures due to earthquakes. b) Clarifying mechanisms of permeability enhancement during earthquakes. c) Highlighting the substantial volumes in motion within the Earth's interior, which, for instance, could constitute a significant source for the origin of mineral deposits. The findings highlight diverse features of the complex interplay between hydrogeological and tectonic processes at challenging spatial and temporal scales.

Increasing groundwater levels (GWL) may become one of the most serious issues for Odessa City, Ukraine. This study investigated the spatial distribution characteristics and multifractal scaling behaviour of groundwater level/depth fluctuation for a Quaternary aquifer in Odessa City using a geostatistical approach and a Multifractal Detrended Fluctuation Analysis (MF-DFA). These two methods were applied to monthly GWL fluctuation time series from 1970 to 2020 to monitor 72 hydrogeological wells situated in different parts of Odessa City. The spatial distribution of GWL revealed an overall trend of decline and recovery from 1970 to 2020 in the study area, except for most of the southern region, where a persistent recovery of groundwater depth was observed. The MF-DFA results suggest that the dynamics of GWL fluctuations have multifractal characteristics in the Odessa City area. In addition, both long-range correlation and fat-tail probability distribution contribute to multifractality. However, long-range correlations among fluctuations made a major contribution to the observed multifractality of the GWL fluctuations time series. The generalized Hurst exponent shows a wide range of change (0.20 < h(q) < 2.85), indicating the sensitivity of GWL fluctuations to changes in small scale factors and large-scale factors. Regarding the long range correlations of GWL depth, the Hurst exponents (q = 2) demonstrated the positive persistence of groundwater depth recovery in the southern region and the persistence of groundwater depth variation in the other regions of the study area. The dynamic changes in GWL depth in the Odessa City area may be affected by both natural structural and anthropogenic factors.

Groundwater use for domestic and agricultural purposes is every day in rural communities. However, groundwater quality in those communities is still being determined due to the lack of water quality monitoring programs. The purpose of this study was to evaluate groundwater quality in rural communities using physiochemical parameters. Eight communities using communal boreholes were selected. Water samples were analysed for temperature, pH, electrical conductivity, total dissolved solids (TDS), ammonia, nitrate, and nitrite as Nitrogen. The pH means ranged from 6.6 to 8.1, whereas high TDS levels of 1390 mg/L and 1470 mg/L were observed in two boreholes. Three boreholes had higher electrical conductivity. Two boreholes had elevated nitrate levels of 15 and 21.5 mg/L. The high nitrate level correlates with the pH, EC, and TDS values. Our results suggest that high nitrate levels measured in communities’ boreholes pose ill health to the community, especially children, infants, and elders. Prenatal exposure to high nitrate has been found to have acute health effects in infants. Therefore, there is a need for further longitudinal studies on health risks among vulnerable groups in these communities.

The key goal of the current study was to determine suitable areas of water pumping for drinking and agricultural harvest in Tabriz aquifer, located in East Azerbaijan province, northwest Iran. In the study area, groundwater is the key foundation of water for drinking and farming requirements. Groundwater compatibility study was conducted by analyzing Electrical conductivity (EC), Total dissolved solids (TDS), Chloride (Cl), Calcium (Ca), Magnesium (Mg), Sodium (Na), Potassium (K), Sulfate (SO4), Total hardness (TH), Bicarbonate (HCO3), pH, carbonate (CO3) and Sodium Adsorption Ratio (SAR) obtained from 39 wells in the period of 2003 to 2014. For this purpose, the Water Quality Index (WQI) and irrigation water quality (IWQ) index were utilized. The WQI index zoning exposed that the groundwater of the study area for drinking purposes is categorized as excellent, good and poor water. Most drinking water harvested for urban and rural areas are in the class of 'excellent water'. The results revealed that about 37 percent (296 km2) of groundwater has high compatibility, and 63 percent of the study area (495 km2) has average compatibility for agricultural purposes. The trend of IWQ and WQI indexes demonstrates that the groundwater is getting worse over the time.

Groundwater contamination by nitrate and organic chemicals (e.g. 1,4-dioxane) is a growing worldwide concern. This work presents a new approach for simultaneously treating nitrate and 1,4-dioxane, which is based on UV sensitization of nitrate and sulfite, and the production of reactive species. Specifically, water contaminated with nitrate and 1,4-dioxane is irradiated by a UV source (< 250 nm) at relatively high doses, to sensitize in-situ nitrate and generate HO•. This leads to the oxidation of 1,4-dioxane (and other organics), and the (undesired) production of nitrite as an intermediate. Subsequently, sulfite is added at an optimized time-point, and its UV sensitization produces hydrated electrons which reacts and reduces nitrite. Our results confirmed the effectivity of the proposed treatment: UV irradiation of nitrate (at > 5 mg N/L) efficiently degraded 1,4-dioxane, while producing nitrite at levels higher than 1 mg N/L (its MCL in drinking water). Adding sulfite to the process after 10 minutes of irradiation reduced the concentration of nitrite, without affecting the degradation rate of 1,4-dioxane. The treated water contained elevated levels of sulfate; albeit at much lower concentration than its MCL. Treating water contaminated with nitrate and organic chemicals (often detected concomitantly) typically requires several (expensive) treatment processes. The proposed approach may present a cost-effective alternative, employing a single system for the treatment of nitrate and organic contaminants

This paper focus on the modeling and time-domain analyzing method of piecewise-smooth fractional-order circuit systems. Firstly, an analytical framework is constructed based on a generalized piecewise-smooth two-port impedance network model, which takes the topological characteristics of Dickson type switched-capacitor converters (SCCs) as examples, and considers the fractional-order characteristics of class-2 X7R ceramic capacitors, which are widely used in SCCs. Secondly, the time-domain analyzing method for such a piecewise-smooth fractional-order circuit system is developed, numerical solutions are obtained, and the influence of the fractional-order capacitor on the power conversion efficiency of the system are revealed. Finally, in order to validate the analysis, both numerical simulation and experiments are provided in the work, the results of which confirm that, the proposed fractional-order analytical framework can capture the power loss mechanism of piecewise-smooth fractional-order circuit systems more effectively than the traditional integer-order based approach, thus benefiting the design of circuit systems.

Among the many Lysosomal Storage Disorders (LSDs) that would benefit from the establish-ment of novel cell models, either patient-derived or genetically engineered, is Mucopolysaccha-ridosis type II (MPS II). In fact, even though a specific therapeutic approach does exist for this disorder (Enzyme Replacement Therapy, ERT, with recombinant human IDS) and haematopoiet-ic stem cell transplantation (HSCT) may also hold promise whenever the disorder is diagnosed soon enough, both approaches have their own drawbacks. Here we present our results on the establishment and characterization of two MPS II pa-tient-derived stem cell line(s) from deciduous baby teeth. To the best of our knowledge, this is the first time a stem cell population is isolated from LSD patient samples obtained from the oral cavity. Taking into account our results on the molecular and biochemical characterization of those cells and our first insights on their subcellular MPS phenotype, we consider these cells will be a valuable tool for both pathophysiological assessments and drugs screenings. Ultimately, we believe patient-derived dental pulp stem cells (DPSC) may represent a feasible alternative to induced pluripotent stem cells (iPSC) in many labs with standard cell culture con-ditions and limited (human and economic) resources.

In this study we discuss critical issues in modelling the structure and function of lymph nodes (LNs), with emphasis on how LN physiology is related to its multi-scale structural organization. In addition to macroscopic domains such as B-cell follicles and the T cell zone, there are vascular networks which play a key role in the delivery of information to the inner parts of the LN, i.e., the conduit and blood microvascular networks. We propose object-oriented computational algorithms to model the 3D geometry of the fibroblastic reticular cell (FRC) network and the microvasculature. Assuming that a conduit cylinder is densely packed with collagen fibers, the computational flow study predicted that the diffusion should be a dominating process in mass transport than convective flow. The geometry models are used to analyze the lymph flow properties through the conduit network in unperturbed- and damaged states of the LN. The analysis predicts that elimination of up to 60–90 % of edges is required to stop the lymph flux. This result suggests a high degree of functional robustness of the network.

Variations in groundwater levels that are noticed in different parts of the world are typically the primary focus of research carried out in hydrology. The fluctuating levels of groundwater can be ascribed to several different factors, some of which include an increase in the demand for water, inappropriate irrigation practices, improper management of soil, and unregulated extraction from aquifers. It is necessary to effectively manage groundwater resources to have a trustworthy method of measuring and forecasting groundwater levels. The dynamics of groundwater are inherently uneven and difficult to understand. As a result, applying methods driven by data could potentially yield significant gains in hydrology. In this study, two data-driven models were utilized to estimate groundwater levels at a total of 4 monitoring wells located in Colorado state, USA. These models included ARIMA and ANN. The comparative analysis of the algorithms made use of a data set that had one month's worth of information from each of the years 1980 to 2019. The models were put through their paces, and the results of those tests were statistically and visually assessed. To evaluate the relative accuracy and precision of the models, the mean absolute error (MAE), mean square error (MSE), and root-mean-square error (RMSE) were used. When compared to ARIMA, the analysis demonstrates that ANN can produce the most accurate forecasts of groundwater levels in Colorado state USA.

A Water demand per capita will rise in the Arab world as a result of climate change and population expansion. One of the most important aims in coping with population increase around the world is to conserve water supplies. As a result, the Kingdom of Saudi Arabia constructed Al Wajeed Water Treatment System to meet the demands of the southern population. This research aims to assess the drinking water quality produced from the AlWajeed Water Treatment System. Monthly water samples were collected (January 2018 to January 2021) from the Al Wajeed Water Treatment Framework (4sites), extending to governorates; Bishah`s distribution system (5sites) and Tathleeth`s distribution system (7sites). Water quality criteria, such as physical, chemical, and microbiological parameters, revealed that the majority of water samples collected from the Al Wajeed Water Framework and its environs are of a good quality matched the national and international standards. Few sites showed water quality criteria, such turbidity, fluoride and total coliform did not comply with national and global standards. The obtained results explained the importance of monitoring and follow-up programs for drinking water criteria. In addition, they can help the authorities and stakeholders in the sustainable development.

Groundwater contamination is an ever-growing environmental issue that has attracted much and undiminished attention for the past half century. Groundwater contamination may originate from both anthropogenic (e.g., hydrocarbons) and natural compounds (e.g., nitrate and arsenic); to tackle the removal of these contaminants, different technologies have been developed and implemented. Recently, bioelectrochemical systems (BES) have emerged as a potential treatment for groundwater contamination, with reported in situ applications that showed promising results. Nitrate and hydrocarbons (toluene, phenanthrene, benzene, BTEX and light PAHs) have been successfully removed, due to the interaction of microbial metabolism with poised electrodes, in addition to physical migration due to the electric field generated in a BES. The selection of proper BESs relies on several factors and problems, such as the complexity of groundwater and subsoil environment, scale-up issues, and energy requirements that need to be accounted for. Modeling efforts could help predict case scenarios and select a proper design and approach, while BES-based biosensing could help monitoring remediation processes. In this review, we critically analyze in situ BES applications for groundwater remediation, focusing in particular on different proposed setups, and we identify and discuss the existing research gaps in the field.

Research subjects of this study are four representative locations in the industrial complex, in the city of Banja Luka, Republic of Srpska, Bosnia and Herzegovina. 16 polycyclic aromatic hydrocarbons (PAHs) (∑16PAHs), humus and pH were determined. The main objective of the paper is to determine the concentration levels, to assess the probable sources of PAHs contamination in soil and groundwater and to determine the ecological risk. The ∑16PAHs in soil (at depths of 30 cm, 100 cm, 200 cm, 300 cm and 400 cm) ranged from 0.99 to 2.24 mg/kg, from 0.34 to 0.46, from 0.24 to 0.32, from 0.13 to 0.27 and from 0.13 to 0.47, with mean values of 1.70 mg/kg, 0.40 mg/kg, 0.28 mg/kg, 0.20 mg/kg and 0.26 mg/kg, respectively. The ∑16PAHs in groundwater ranged from 0.23 to 4.50 mg/m³, with a mean value of 1.42 mg/m³. Surface soil and groundwater are heavily contaminated. All values of ∑PAHs in soil layers were lower in the depths of the soil. Factor analysis indicates three sources of contamination, i.e. principal component (PC) PC1 (pyrogenic), PC2 (petrogenic) and PC3 (biomass), with 52.39%, 26.14% and 8.46% of the total variance, respectively. ∑PAH and PAHs indicate high ecological risk for most PAHs, which decreases with soil depth.

In this study, the effect of NaOCl (10–200 ppm of Cl2) on the inactivation of human norovirus (HuNV) GII.4 and hepatitis A virus (HAV) in groundwater was investigated using PMA/RT­qPCR. Initially, 4.00 log copies/μL of HuNV GII.4 or 5.50 log copies/μL of HAV were artificially inoculated in ground water. The titers of HuNV GII.4 and HAV decreased significantly (p < 0.05) with increasing Cl2 concentrations. Ground water was treated with 10, 30, 50, 100, 150, and 200 ppm of Cl2, and the viable HuNV GII.4 was significantly (p < 0.05) reduced to 3.28 (0.21 log reduction), 3.18 (0.31 log reduction), 3.01 (0.48 log reduction), 2.75 (0.74 log reduction), 2.54 (0.95 log reduction), and 2.34 (1.15 log reduction) log copies/μL, respectively. The viable HAV was also significantly (p < 0.05) reduced to 4.99 (0.23 log reduction), 4.76 (0.46 log reduction), 4.55 (0.67 log reduction), 4.21 (1.01 log reduction), 3.89 (1.33 log reduction), and 3.64 (1.58 log reduction) log copies/μL, respectively. The decimal reduction time (D-value) (1-log reduction) of HuNV GII.4 and HAV infectivity in ground water was predicted as 116.7 and 98.9 ppm of Cl2, respectively using the first-order kinetics model (HuNV GII.4 ; y = - 0.0054x + 3.3585, R2= 0.97, HAV ; y = - 0.0091x + 5.0470, R2= 0.97). The result specifically suggests that 150–200 ppm Cl2 can potentially be used for the inactivation of > 1 log copies/μL HuNV GII.4 and HAV in ground water.

Disasters related to climate change on our water resources are on the rise in terms of scale and severity. Therefore, predicting groundwater levels (GWL) is a crucial means to aid adaptive capacity towards disasters related to climate change in our water resources. In this study Gradient Boosting (GB) regression modelling approach for GWL prediction as a function of rainfall and antecedent GWL is used. Firstly, we sought to demonstrate the effects of rainfall changes on our groundwater resources through a Mann-Kendall trend analysis. Secondly, we evaluated the relationship between the input and response variables and determined the optimal lag times between the variables using autocorrelations and cross-correlations. Lastly a predictive model was developed for eight groundwater stations in the Upper Crocodile. 50 % of the groundwater stations revealed declining trends, while 25% had no trends and the other 25% showed an increasing trend. Generally low cross-correlation maximum (CCmax) were obtained, with the highest CCmax being 0.299 at an optimal lag of 2-month. While the highest autocorrelation was 0.969 at a 1-month lag. The best groundwater predictive model had R2 and MSE of 0.66 and 0.06, respectively. The stations that generally performed better had both high autocorrelation and cross-correlation coefficients. GB model performed satisfactorily in predicting GWL for most of the stations in the study area. Therefore, GB can be used for GWL prediction in the Upper Crocodile.

Ternate Island is a volcanic island resulting from the activity of the Gamalama Volcano which is located in the northern Maluku archipelago, Indonesia. Ternate Island is famous as the only island that produces special spices and is the zero point of the world's spice route because the main producer of cloves is here. As a small island, Ternate Island has several limitations including the availability of water resources. Given the scarcity of surface water on the island of Ternate, groundwater in shallow aquifers and deep aquifers is the main source of fresh water which is important for irrigation activities, tourism, services and supporting urban and industrial infrastructure, as well as drinking water needs for people who live densely and are concentrated in the east. and the southern part of the island which is now the city of Ternate. The phenomenon of groundwater utilization in Ternate City is generally massively carried out to support economic activities in the city of Ternate. The purpose of this study was to evaluate the potential and quality of groundwater resources which are an important part of water management on the island of Ternate by microzoning the quality of groundwater for the sustainability of the city which is famous as the world's spice city based on its groundwater potential. Determination of groundwater samples as many as 67 wells distributed on the island of Ternate, 58 well sample points were categorized as free aquifers (MA-SG) and 7 points of depressed aquifers (SB). Ternate island area of ​​102 km2 with volcanic geology in 3 rock categories. Geological distribution also affects the hydrogeological potential and groundwater quality on the island of Ternate. Piper's trilinear diagram and stiff diagram methods were adopted for the assessment of the main ion quality of groundwater and the distribution of groundwater potential was interpolated with cubic splines to obtain correlations between sample points based on basic parameters of volcanic hydrogeology. The total potential for groundwater recharge is 1,291 million m3/year, there are 5 groundwater quality zones spread among 67 sample points with 76% distribution of elements Calcium Bicarbonate (CaCO3), Sodium Bicarbonate (NaHCO₂), magnesium bicarbonate Mg(HCO3)2 and widely distributed on the island of ternate, while 25% magnesium chloride (MgCl2) and potassium chloride (KCL) are scattered locally on the island of ternate. On an ongoing basis the bicarbonate facies micro-zonation is hydrogeochemical with local flow interactions in volcanic deposits, where infiltration tends to be close to the groundwater sample point, while the chloride facies is a groundwater zone that is correlated with flow patterns from upstream to downstream and has interacted with magma or was intruded. seawater is characterized by high Ca and TDS.

Groundwater models serve as support tools to among others: assess water resources, evaluate management strategies, design remediation systems and optimize monitoring networks. Thus, the assimilation of information from observations into models is crucial to improve forecasts and reduce uncertainty of their results. As more information is collected routinely due to the use of automatic sensors, data loggers and real time transmission systems; groundwater modelers are becoming increasingly aware of the importance of using sophisticated tools to perform model calibration in combination with sensitivity and uncertainty analysis. Despite their usefulness, available approaches to perform this kind of analyses still present some challenges such as non-unique solution for the parameter estimation problem, high computational burden and a need of a deep understanding of the theoretical basis for the correct interpretation and use of their results, in particular the ones related to uncertainty analysis. We present a brief derivation of the main equations that serve as basis for this kind of analysis. We demonstrate how to use them to estimate parameters, assess the sensitivity and quantify the uncertainty of the model results using an example inspired by a real world setting. We analyze some of the main pitfalls that can occur when performing such kind of analyses and comment on practical approaches to overcome them. We also demonstrate that including groundwater flow estimations, although helpful in constraining the solution of the inverse problem as shown previously, may be difficult to apply in practice and, in some cases, may not provide enough information to significantly constrain the set of potential solutions.

Heavy metals contamination in groundwater often occurs in various industrial processes. Stud-ies have confirmed that polysulfide could reduce hexavalent chromium to trivalent chromium, achieving the effect of in-situ stabilization. For other heavy metals contamination in groundwa-ter, whether polysulfide also had a stabilizing ability to achieve in-situ remediation. This re-search focused on heavy metals except for chromium that often contaminated in groundwater, including lead, nickel, zinc, copper, and cadmium to explore the feasibility of using calcium polysulfide (CaSx) as an in-situ stabilization technology for these heavy metals contamination groundwater. Results showed that CaSx had a great removal efficiency for heavy metals lead, nickel, zinc, copper, and cadmium. However, for nickel, zinc, copper and cadmium, when CaSx was added excessively, complexes would be formed, causing the result of re-dissolve and this would also reduce the removal efficiency. Since it is difficult to accurately control the dosage of agents for in-situ groundwater remediation, the concentration of re-dissolved nickel, zinc, cop-per, and cadmium may not be able to meet the groundwater control standards. CaSx had high lead removal efficiency, and it would not cause re-dissolution due to excessive CaSx dosing. CaSx can be used as an in-situ stabilization technique for lead contaminated groundwater.

This study evaluates spatial analyses of groundwater quality and environmental changes to obtain information on the groundwater contamination in the Permian Basin, Texas. Coupled with the U.S. government’s open data, these analyses can identify regions where environmental change could have potentially effected groundwater quality. A total of thirty-six wells were selected within the six counties: Andrews, Martin, Ector, Midland, Crane, and Upton. Spatial distribution maps were created for six different parameters: pH, total dissolved solids (TDS), chloride, fluoride, nitrate, and arsenic. Total groundwater quality maps incorporate all the contaminants and denote regions of poor, medium, and optimum conditions. To identify spatial changes in groundwater quality, maps were separated into two different time intervals, 1992-2005 and 2006-2019. We found that groundwater contamination resulted primarily from the mobilization of the contaminant from natural sources or anthropogenic activities such as chemical fertilizers. Overall, groundwater quality decreased during the study period from 1992 to 2019 as population and urban growth began to develop in the Permian Basin. This study contributes on understanding of the response of groundwater quality associated with environmental change in the Permian Basin. Therefore, this research provides important information for groundwater managements in developing plans for the use of water resource in the future for Texas.

Groundwater plays a pivotal role as the largest potable water sources in Bangladesh. However, the quality of the groundwater faces challenges due to xenobiotic compounds in it. Excess amount of arsenic (As) has already been found in groundwater in many parts of Bangladesh. Thus, this study was conducted to assess the water quality and associated human health risk in central Bangladesh. A total of 99 groundwater samples from the central part of Bangladesh were analyzed to assess human health risk due to high level of nitrate (NO3-) and other trace elements i.e. arsenic (As), iron (Fe), and manganese (Mn). It was found that NO3- concentration (253.17 mg/L) in the groundwater samples exceeds the recommended guideline value by the WHO (50 mg/L). Moreover, this study area also characterized with elevated concentration of As (19.44 µg/L), Fe (811.35 µg/L), and Mn (455.18 µg/L) in the groundwater. Non-carcinogenic human health risk was calculated by justifying HQ (Hazard Quotient) and HI (Hazard Index) and attributed potential conjunctive human health risks due to NO3-, As, Fe and Mn in the study area. Moreover, high carcinogenic risk was found due to As contamination in the groundwater samples in the study area.

Ca Mau Peninsula (CMP), the southernmost region of the Mekong Delta, is facing a severe loss of land and freshwater. Particularly, the groundwater resources in the complex multilayered aquifer system of CMP are subject to salinization processes, which are not yet fully understood. In this study, an existing groundwater flow model for the CMP was enhanced to a density-dependent transient transport model using the FEFLOW software package, which is based on the finite element method. The study focuses on simulating groundwater salinity in order to better understand the dynamics of groundwater salinization and potential saltwater intrusion pathways in the study area. Time series of Total Dissolved Solids (TDS) concentrations at observation wells were used to compare simulated and observed salinity data in different aquifers. The model allows a multi-factorial evaluation of the spatial groundwater salinity and could also confirm significant inter-annual variability, particularly in the case of shallow aquifers due to the influence of tides and seasonal rainy/dry seasons. Using sensitivity analysis, leakage from upper saline aquifers into lower freshwater aquifers through natural hydrogeological windows and poorly sealed boreholes was identified as a potential major cause for groundwater salinization occurring in the region. The results obtained can serve as an important basis for developing decision-making tools to promote the sustainable use of water resources on the CMP in the future.

Arsenic is naturally present in many geological formations around the world and is a major source of groundwater contamination. Bolivia is not exempt from this problem. Physical-chemical studies of water quality in deep and shallow wells have determined the presence of arsenic in some areas of the Bolivian Altiplano, valleys, and plains. In the Lake Poopó basin, water from shallow wells (up to 30 m) has arsenic concentrations that exceed the Bolivian drinking water standard and the WHO recommendation of 10 μg-As/l by up to 25 times. In peri-urban areas of Cochabamba, the arsenic content in groundwater is up to 113 μg-As/l. chronic exposure to arsenic is associated with neurological and dermatological problems and carcinogenic effects. To date, no measures have been taken to mitigate the arsenic problem for the rural population, who often rely on arsenic-contaminated water as their only source of drinking water. This contamination represents a serious threat to the health and economic well-being of the inhabitants and ecosystem in these areas. In this work, for arsenic removal, iron and iron oxide nanoparticles obtained from recycling metal chips by top-down and bottom-up technology have been used for arsenic adsorption in an experimental filter combined with other artisanal filtering materials in the form of layers. The results have shown that water contaminated with arsenic after passing through the filter reduces the concentration of total arsenic filtered from 83, 52 ppb to less than 5 ppb, less than the Bolivian standard 512 of 10 ppb for drinking water.

Karst aquifers show dissolution/precipitation processes of the minerals present in the carbonate rocks. The Ring of Cenotes (RC) extends along the edge of the Chicxulub crater, in the limestone platform of the Yucatan Peninsula (YP), where groundwater shows preferential flow paths toward the coast near Celestun and Dzilam Bravo towns. This study aimed to describe the regional hydrogeochemical evolution of groundwater of the RC, and its association with the dissolution/precipitation of the minerals present along its path to the ocean. To achieve this aim, we: a) characterized groundwater's hydrogeochemistry; b) determined the calcite, dolomite, and gypsum saturation indexes (reaction phases with the groundwater) in the study area; c) proposed a hydrogeochemical model developed through PHREEQC using an inverse modelling approach. The model predictions confirmed that there are two evolution pathways of the groundwater consistent with the preferential flow paths suggested in a previous regionalization of the RC. On the western path, where groundwater flows towards Celestun, an important marine intrusion influences the hydrogeochemical processes and represents a risk for the prevalence of freshwater. On the eastern path, where groundwater flows toward Dzilam Bravo, the hydrogeochemistry in the sinkholes correlates well with rainfall, suggesting a higher vulnerability during droughts than during rainy periods.

Energy system models have become indispensable to shape future energy systems by providing insights into different trajectories. However, sustainable systems with high shares of renewable energy are characterized by growing cross-sectoral interdependencies and decentralized structures. To capture important properties of increasingly complex energy systems, sophisticated and flexible modelling tools are needed. At the same time open science becomes increasingly important in energy system modelling. This paper presents the Open Energy Modelling Framework (oemof) as a novel approach in energy system modelling, representation and analysis. The framework forms a toolbox to construct comprehensive energy system models and has been published open source under a free license. With a collaborative development based on open processes the framework seeks for a maximum level of participation and transparency to facilitate open science principles in energy system modelling. Based on a generic graph based description of energy systems it is well suited to flexibly model complex cross-sectoral systems and incorporate various modelling approaches. This makes the framework a multi-purpose modelling environment for modelling and analyzing different systems ranging from an urban to a transnational scale.

The effect of climate change plays a significant role on groundwater level variations and crop yield. The change in climate leading to increased temperatures, decreased rainfalls and extreme drought conditions ultimately cause low groundwater level and crop yield. Judicious groundwater management technology viz., water recharge options, need based irrigation, crop selection, must be adapted for further increasing the water table level in soil ecosystem. Additionally, climate change impacts combined with changes in agricultural water use can affect groundwater dynamics. Increased irrigation demand and decreased summer precipitation can lower groundwater levels, impacting crop production. Overall, climate change affects both groundwater resources and crop yield highlighting the need for sustainable water management practices and consideration of soil properties in agricultural modelling. The authors carefully selected relevant research articles addressing the impact of climate change on ground water level in Asian countries. The review highlights the use of machine learning method to ground water level and crop yield modelling. According to the study, machine learning techniques have made significant contributions to predicting groundwater level changes and crop yield with higher accuracies, high performance and less running time.

With the rapid development of cities in northwest China, there has been an increasing focus on groundwater pollution in plateau cities, specifically the common occurrence of nitrate pollution. The special climatic, geological, and geomorphological characteristics of plateau and river valley cities contribute to distinct groundwater chemical characteristics. Therefore, the formation and evolution process of groundwater nitrate contamination differs from that of plain cities. To explore these issues, we conducted an analysis of eight major ions in various groups of water samples from rivers, springs, and groundwater in Haidong. By utilizing factor analysis and correlation analysis, we were able to identify the characteristics and formation of groundwater chemistry and nitrate pollution in Haidong. Our findings reveal that the chemical characteristics of groundwater in Haidong are primarily controlled by rock weathering, mineral dissolution, and evaporation, leading to the formation of highly mineralized groundwater. Additionally, the excessive nitrate content in certain areas is a result of domestic sewage discharge and agricultural fertilizer use, exceeding Chinese drinking water health standards. Furthermore, for cities located in valleys, the geological structure significantly impacts the nitrate content of groundwater in different regions. Areas with obstructed groundwater flow tend to have higher nitrate levels, while regions with unobstructed groundwater experience lower nitrate concentrations. Notably, shallow groundxwater is more vulnerable to nitrate pollution compared to deep groundwater. This study holds great significance in understanding the chemical characteristics of groundwater and the formation and evolution of nitrate pollution in highland river valley cities.

High nitrate and fluoride contamination in groundwater cause a variety of disorders, including methemoglobinemia, teratogenesis, and dental and skeletal fluorosis. The present work assesses the non-carcinogenic health risks posed by nitrate and fluoride in infants, children, and adults using the USEPA method. Groundwater samples were collected from 36 wells and boreholes in three central Saudi Arabia study areas. Nitrate concentrations varied from 0.70 to 47.00 mg/L. None of the 36 studied boreholes had nitrate levels that exceeded WHO guidelines (50.00 mg/L). Fluoride ranged from 0.63 to 2.00 mg/L, and 30.55% of the fluoride samples (11 out of 36) exceeded the WHO recommendations for acceptable drinking water (1.5 mg/L). The average hazard index (HI) values for adults, children, and infants were 0.99, 2.59, and 2.77, respectively. Water samples surpassed the safety level of 1 for adults, children, and infants at 44.44, 97.22, and 100%, respectively. Accordingly, water samples from Jubailah and a few from Wadi Nisah may expose infants, children, and adults to non-cancer health concerns. Infants and children are more vulnerable to non-carcinogenic health risks than adults, possibly due to their lower body weight.

This note makes available five years of data gathered in a measurement site equipped with a micrometeorological station and two monitoring wells. Series of data of hydrological and atmospheric variables allow to estimate the flux of water across the atmosphere-land interface and to calculate the water budget, that are crucial topics in climate and environmental sciences. The measures of water-table began during 2017, one of the driest year of the whole instrumental period of climate history for the Central Mediterranean. Data from the micrometeorological station have been used to construct two more datasets of daily and monthly cumulative values of different terms of the surface water budget, from which the groundwater infiltration has been estimated. A significant decreasing trend characterizes both the data time series of piezometric heights and estimated infiltration in the considered period. All the data are collected in 2017-2022 datasets that are available in the supplementary material.

Recognizing trust as a pivotal element for success within Human-Robot Collaboration (HRC) environments, this article examines its nature, exploring the different dimensions of trust, analysing the factors affecting each of them, and proposing alternatives for trust measurement. To do so, we designed an experimental procedure involving 50 participants interacting with a modified 'Inspector game' while we monitor their brain, electrodermal, respiratory, and ocular activities. This procedure allowed us to map dispositional (static individual baseline) and learned (dynamic, based on prior interactions) dimensions of trust considering both demographic and psychophysiological aspects. Our findings challenge traditional assumptions regarding the dispositional dimension of trust and establish clear evidence that the first interactions are critical for the trust-building process and the temporal evolution of trust. By identifying more significant psychophysiological features for trust detection and underscoring the importance of individualized trust assessment, this research contributes to understanding the nature of trust in HRC. Such insights are crucial for enabling more seamless human-robot interaction in collaborative environments.

A non-steady state mathematical model of amino acid (phenylalanine (Phe)) and mineral salt (NaCl) solution separation by neutralization dialysis (ND) carried out in a batch mode is proposed. The model takes into account the characteristics of membranes (thickness, ion-exchange capacity and conductivity) and solutions (concentration, composition), as well as the flow rate of the solution in the dialyzer compartments. As compared to previously developed models, the new one considers the local equilibrium of Phe protolysis reactions in solutions and membranes and, also, the transport of all the phenylalanine forms (zwitterionic, positively and negatively charged) through membranes. A series of experiments on ND demineralization of NaCl and Phe mixed solution was carried out. In order to minimize Phe losses, the solution pH in the desalination compartment was controlled by changing the concentrations of the solutions in the acid and alkali compartments of the ND cell. The validity of the model was verified by comparison of simulated and experimental time dependencies of solution electric conductivity and pH, as well as the concentration of Na+, Cl– ions and Phe species in the desalination compartment. Based on the simulation results, the role of Phe transport mechanisms in the losses of this amino acid during ND was discussed.

Nodes in wireless sensor networks (WSN) are characterized particularly by their limited power and memory capabilities. Limited memory is an important parameter as it defines the size of the operating system and the processing code. As established previously, energy and memory efficiency is the most important evaluation factors of WSNs as they are directly related to data loss and network lifetime. However, based on our simulation results, memory efficiency determines the selection or abandon of nodes by the botmaster for the propagation of bots in an IoT infrastructure. Consequently, the node’s memory efficiency determined the spread of bots in the network and provides defense actors with an insight of the botmaster behavior for mitigation of the attack. Conventional botnet propagation and mitigation models did not consider the impact of node’s memory efficiency in the IoT platform. To address this gap, we build IoT-SIEF, a novel propagation model with forensic capability that will analyze command and control propagation behavior based on the perspective of the node’s memory efficiency. IoT-SIEF model used to explore the dynamics of propagation using numerical simulation with more than 50% outperform other models in mitigating the number of secondary bots. Consequently, it can serve as a basis for assisting the planning, design, and defense of such networks from the investigator's point of view.

The process of modelling energy systems is accompanied by challenges inherently connected with mathematical modelling. However, due to modern realities in the 21st century, existing challenges are gaining in magnitude and are supplemented with new ones. Modellers are confronted with a rising complexity of energy systems and high uncertainties on different levels. In addition, interdisciplinary modelling is necessary for getting insight in mechanisms of an integrated world. At the same time models need to meet scientific standards as public acceptance becomes increasingly important. In this intricate environment model application as well as result communication and interpretation is also getting more difficult. In this paper we present the open energy modelling framework (oemof) as a novel approach for energy system modelling and derive its contribution to existing challenges. Therefore, based on literature review, we outline challenges for energy system modelling as well as existing and emerging approaches. Based on a description of the philosophy and elementary structural elements of oemof, a qualitative analysis of the framework with regard to the challenges is undertaken. Inherent features of oemof such as the open source, open data, non-proprietary and collaborative modelling approach are preconditions to meet modern realities of energy modelling. Additionally, a generic basis with an object-oriented implementation allows to tackle challenges related to complexity of highly integrated future energy systems and sets the foundation to address uncertainty in the future. Experiences from the collaborative modelling approach can enrich interdisciplinary modelling activities. Our analysis concludes that there are remaining challenges that can neither be tackled by a model nor a modelling framework. Among these are problems connected to result communication and interpretation.

Zagros is an important region with high quality and quantity karstic water resources in the Middle East. This region provides a dominant part of potable and agricultural water needs for its inhabitants as well as agricultural water needs for nearby regions. Therefore, studying karstic water resources in Zagros by accurate methods such as stable isotopes techniques is very important. In this investigation, hydrological characteristics of groundwater resources including groundwater origin, recharge rate and recharge elevation have been studied using stable isotopes (¹⁸O and ²H). The results show that stable isotopes signatures in groundwater resources show notable variations across Zagros and groundwater resource mainly plot on south and west Zagros meteoric water lines. In addition, recharge elevation and recharge rate in groundwater resources also show significant variations in Zagros. Finally, the stable isotopes signatures in precipitation and groundwater has been used to study the role of each dominant air mass (contribution percentage of precipitation events originate from each air mass) in groundwater resources recharge using Simmr package in R language. Overall, groundwater resources in Zagros is recharged by precipitation events originate from various air masses and they have various recharge rates and recharge elevations.

Analysis of water resources of this area was carried out in order to assessing the water quality by determining the concentrations of Cations, Anions, Heavy metals, Trace elements, PH, Alkalinity, Total Dissolved Solids and microbial loads in water samples. Ten (10) water samples were collected from the study area - samples each of rain water, two pond waters - 1 and 2, stream water, four (4) hand-dug wells, hand pump water and a motorized borehole. The results obtained were compared with WHO standards and it showed that all the cations in water samples are within the limits. The water samples at locations B, E, F, G, H, I, and J have high alkalinity and HC0^-₃ content. The heavy metals (Pb, Ni and Cd) and trace elements (Fe and Cu) are dominantly high in the surface waters. Microbiological substances in the water samples from the study area revealed indicator organisms higher than the WHO standard for drinking water. Samples obtained from location G, I and J recorded an absence of E. coli and are fit for human consumptions but needed to be treated due to high MPN (Most Probable Number) index of viable microorganisms as against WHO standard. This research showed that the water resources of the study area are gradually polluted and in the near future may not be good for drinking.

Based on the analysis of hydrochemical data of 18 samples of shallow groundwater around Hancheng mining area in Guanzhong Basin, Gibbs semi-logarithmic diagram and Piper diagram were used to study the hydrogeochemical behavior of shallow groundwater around Hangcheng mining area in Guanzhong Basin. Chemical composition analysis showed that most of the groundwater was SO₄ · Cl-Ca · Mg type, accounting for 61.1 %. Hydrogen and oxygen isotope data show that groundwater in the study area is recharged by modern precipitation. The main chemical components of most groundwater are Ca²⁺, Mg²⁺, HCO₃^-, Cl^-and SO₄^2-. Ca²⁺, Mg²⁺, and HCO₃^- are mainly dolomite, calcite, and gypsum dissolution precipitation results. Na⁺ and Cl^- originate from the dissolution of halite. The main ion chemistry of shallow groundwater in this area is controlled by rock weathering, and pyrite oxidation is an important factor affecting SO₄^2-concentration. The research results will help analyze the formation mechanism of chemical components and provide some basic data for the evolution of mine water in this area in the future.

The global rising demand for exploiting limited shared groundwater resources, coupled with significant water deficit, especially in arid and semi-arid regions, has led to escalating conflicts among stakeholders. As such, using Bankruptcy Theory methods can be an appropriate response to the reallocation of resources. This study introduces a novel approach to weighted Bankruptcy, where the relative importance of stakeholders is determined by their contributions to sustainable development, and the impact of their claims on the shared groundwater resources is considered. The framework is implemented in a two-level bankruptcy process including the plains and their beneficiaries (agriculture, drinking and industry). The proposed two-level weighted bankruptcy process applies to the Neyshabour-Ataiyeh-Sabzevar plains in Iran. The process is implemented for two scenarios including the Baseline scenario related to the present status of demands and the Future scenario associated with the estimated demands for the year 2041. To compare the weighted proposed method with the other weighted methods such as Proportional (WPRO), Constrained Equal Awards (WCEA), Pinile (WPIN), Talmud (WTAL), Constrained Equal Losses (WCEL), Modified Constrained Equal Losses (MWCEL), two categories including the deficit-based and resource-based approaches are considered. According to the stability analysis using the Bankruptcy Allocation Stability Index (BASI) method, among the deficit-based methods, the novel approach is chosen as the preferred method for the beneficiaries’ reallocation like the Sabzevar’s beneficiaries. Accordingly, it allocates 86.95%, 10.86% and 2.17% of the shared resource to the agricultural, drinking, and industrial demands, respectively. Among the resource-based methods, the WPIN method is selected for reallocation between the stakeholders and their beneficiaries in each level and scenario of reallocation. The novel approach offers a promising solution to the water resource reallocation problem, ensuring a more equitable and sustainable management of shared groundwater resources.

A geophysical technique termed Electrical Resistivity Tomography was applied to identify potential groundwater-bearing zones around Nubutautau village within Viti Levu Island of Fiji. Apparent resistivity data of the subsurface were collected through the electrode assembly along survey lines by injecting current into the subsurface using the ABEM Terrameter LS2. True resistivity data were simulated using the Res2DINVx64 software to produce the final electrical resistivity profiles through an iterative process. Analysis of the resulting modelled profiles revealed the presence of two potential groundwater-bearing zones as potential targets for future drilling. The two targets indicated the presence of potentially saturated vertical fractures through which infiltrating rainwater percolates through the volcanic rock towards a deeper basal aquifer. The identification of the two potential targets demonstrated the great potential of this geophysical technique to effectively inform drilling operations through an evidence-based approach to increase the successful delivery of water security interventions in remote, drought-prone communities of the Pacific.

Groundwater degradation is a global problem linked to irrigation agriculture and aggravated by climate change. In drylands, where aquifer recharge is low, irrigation has emerged as an engine of economic growth. This problem falls under the paradigm of desertification, as it fits the definition of this complex problem in that the degradation of drylands is due to climatic variations and inappropriate human activities. Land Degradation Neutrality (LDN), the response of the United Nations Convention to Combat Desertification to the lack of progress in tackling desertification, is integrated into Sustainable Development Goal 15.3 and provides the adequate framework for implementing effective solutions. LDN prioritizes prevention strategies, and early warning systems coupled to integrated simulation models is a sound approach. We analyze the dynamics of a coastal aquifer in southern Spain, a “desertification landscape” according to the Spanish National Action Plan to Combat Desertification. For this purpose, we have (i) adapted a generic desertification model that considers socio-ecological systems as a particular case of predator-prey systems; and (ii) coupled to this model a risk analysis to calculate the probabilities of groundwater salinization under the current scenario of water resources use, driven by the expansion of greenhouse agriculture supported by external water transfer. The risk of desertification is close to 100%: groundwater salinity is 40 dS m-1 (well above tomato tolerance, 3.5 dS m-1), and 2.4 Mm3 yr–1 water transfer is needed to support the 631 ha of greenhouses. This worrying result suggests that complimentary solutions should be promoted to deactivate the ongoing process of desertification. Among them, we propose reclaimed water, diversifying the economy, or promoting crops adapted to aridity. This simulation framework shows how to explore the future of a socio-ecosystem under current scenarios and others that consider climate change, the energy crisis, or the impact of alternative solutions.

Groundwater vulnerability assessment has become a useful tool for groundwater pollution pre-vention. Groundwater vulnerability maps provide useful data to protect groundwater resources. The identification of agricultural patterns is an important issue for optimized land management. The Tagus river watershed is the backbone of this survey. Naturtejo UNESCO Global Geopark, in central inland Portugal, corresponds to a rural territory. Intensive agricultural practices showed a rising tendency in the last decades. The most internationally used method for vulnerability evaluation is the DRASTIC index. In this survey, the DRASTICAI index is introduced. A new at-tribute - Anthropogenic Influence - is here added. Five levels of growing vulnerability, from low to high, can be here acknowledged. Idanha-a-Nova municipality is the most affected by intensive farming activities. A robust assessment of groundwater quality has a key role. Climate change scenarios and water scarcity are important issues in years to come. Therefore, optimized groundwater management is essential to consider in policy-making strategies.

Groundwater is an important role of the environment in natural resources. The major sources of groundwater contamination in this study were open discharges of domestic sewage, inadequate sewerage system, open defecation, septic tanks, soak pits, contaminated water pools, unorganized solid waste dumping and use of fertilizers, pesticides for agriculture deteriorated the condition. In this present study revealed that the physical and chemical characteristics of ground water in different areas of Kannur district in Kerala have been determined different seasons with respect to its suitability for drinking and agricultural purposes. For this study the groundwater samples were collected during pre-monsoon and post-monsoon seasons from 70 wells representing the entire the study area. The groundwater samples were analyzed for Physico-chemical characteristics using standard techniques in laboratory and compared with standards. The samples were analyzed with reference to the WHO and BIS standards. The groundwater quality information of the entire study area have been prepared using statistical and GIS technique for all the parameters. This paper proved in GIS will be helpful for measuring, monitoring and managing the groundwater pollution in the study area and suggested to protect groundwater resources in the environment.

Climate change and over-exploitation are imposing unprecedented threats to the groundwater resource. Globally, groundwater reserves have depleted to the extent that well yield have decreased, pumping cost have risen, and land have irreversibly subsided. In Malawi, groundwater quantity is a national problem, specifically in Mzimba district due to severe droughts. In this study, the spatial and temporal trends of groundwater depletion was assessed using Gravity Recovery and Climate Experiment (GRACE) data and Land Surface Models (LSM) from Global Land Data Assimilation System (GLDAS) and Global Surface Water Explorer (GSWE). The results show that 1. Groundwater storage is depleting at an average rate of-1.0 ± 0.06 cm yr-1(0.1043 km3yr-1) in the study area with high rate of up to -1.2 cm yr-1(0.12516 km3 yr-1) in the western side and as low as –0.4 cm yr-1(0.04172 km3 yr-1) in the eastern part. 2. Groundwater storage increases from -13 cm in November up to 15 cm between May and April. 3. Drought is the primary cause of such depletion trends with correlation between active evapotranspiration and groundwater depletion, and downward surface shortwave radiation and groundwater depletion, at -0.577 and -0.678 respectively. The results from the study reveals the need for the scientific community and the general public to consider groundwater recharge strategies specifically by mitigating climate change to reduce prolonged droughts. The study suggests the need to establish a stand-alone groundwater assessment and monitoring authority for enhanced conservation efforts of the water resource in the country.

Abstract: To explore the interrelationship between groundwater microbial communities and hydrochemical characteristics in Mancheng district, Baoding city, samples from karst groundwater and porous groundwater were collected respectively. The hydrochemical analysis and 16s RNA gene V4-V5 region sequencing method were used to detail the water environmental characteristics and microbial community distribution pattern in the study area. The hydrochemical results reveal significant differences in major ion contents and other hydrochemical indices between karst water and porous water. Microbial community analysis demonstrates that Proteobacteria, Actinobacteria, and Firmicutes are the dominant taxa in both types of water bodies, but their proportions vary significantly in different water bodies. The difference in microbial communities between karst water and porous water reflects the influence of environmental factors such as ion concentration and pH on microbial distribution. Redundancy analysis (RDA) indicates significant associations between microbial community composition and environmental factors in both types of groundwater environments. Studying the distribution pattern of microbial communities and the connection with environmental factors in two types of groundwater provides important basis for interpreting the functional roles of microbes in groundwater ecosystems.

Arsenic is highly toxic, affecting millions of people in many regions of the world. That is why developing economic and efficient technologies is imperative to eliminate it. Sorption techniques are attractive as efficient and inexpensive sorbents can be used. Chitosan is an abundant, naturally occurring, biodegradable, low-cost biopolymer that can be combined with metal oxide to enhance its removability. This work aimed to synthesize a new chitosan-magnetite-based sorbent for arsenic removal. The synthesized sorbent does not present pores, and by FT-IR, functional groups of the chitosan and the presence of As(V) in the sorbent treated with arsenic were identified. The synthesized magnetite was characterized by XRD spectroscopy. Application of the Composite Central Design model showed that 0.22 g of the sorbent at pH 6.0 could remove 27.6% of As(V). Kinetic data, fitted with the pseudo-first and second-order models, indicated an ion exchange sorption and activation energy of 28.1-31.4 kJ mol-1. The isotherms were fitted with the Langmuir model, indicating a favourable monolayer adsorption with high affinity. The sorption energy, calculated by Dubinin-Radushkevich, 9.60-8.80 kJ mol-1, confirms a sorption mechanism mediated by ion exchange. The thermodynamic parameters of the process were ΔG°(-21.7/-19.7 kJ mol-1), ΔH°(16.7 kJ mol-1) and ΔS°(123.3 J mol-1 K-1).

The Baltic Sea coast is one of the geographical areas of Europe most threatened by the current climate change. This issue concerns erosional processes, groundwater flows affecting sea-shore settings. Long term hydrological investigations within the western sector of the Łeba Barrier, northern Poland, based on a network of monitoring stations, coupled with the meteorology records of the past 12 years, revealed significant fluctuations in ground water fluxes from the Baltic Sea on the adjoining mainland. Groundwater resources are negatively affected by sea-level drops in the coastal areas along the southern Baltic coast. The low sea levels strengthen the effects of low precipitation and high temperatures, causing altogether the occurrence of hydrogeological drought in the coastal sandbar areas. Drought periods are characterized by lowering of water-tables in the Slowinski National Park. The obtained results have direct relevance to a long-term assessment of water resources, environmental protection of the climatically most susceptible ecosystems, as well as the tourism management of this popular visitors’ destination.

Recharge is a crucial section of water balance for both surface and subsurface models in water resource assessment. However, quantifying its spatiotemporal distribution at a regional scale poses a significant challenge. Empirical and numerical modeling are the most commonly used methods at the watershed scales. However, integrated model inherently contain a vast number of unknowns and uncertainties, which can limit their accuracy and reliability. In this work, we have proposed integrated SWAT-MODFLOW and Transient Water Table Fluctuation Method (TWTFM) to evaluate the spatiotemporal distribution of groundwater recharge in Anyang wa-tershed, South Korea. Since TWTFM also uses SWAT model percolation output data, calibration was performed for individual models and coupled model. The coupled model was calibrated using daily streamflow and hydraulic head. SWAT-MODFLOW model performed well during the simulation of streamflow compared SWAT model. The study output showed that the study watershed had significant groundwater recharge variations during the simulated period. A sig-nificant amount of recharge happens in the wet season. It contributes about 34% of the average annual precipitation of the region. The direct flow components (surface and lateral) showed sig-nificant contributions when the water balance components were evaluated in the region. TWTFM showed a glimpse to estimate recharge, which requires representative monitoring wells in the study region. Comprehensively, the SWAT-MODFLOW model estimated groundwater recharge with reasonable accuracy in the region.

Human activities mostly impact the trend and direction of surface water, groundwater, and other river basin resources in the watershed in Africa. Human activities influence river flows and the water quality at both highlands and lowlands. A watershed is indeed a conserved area of land that collects rain and snow and empties or penetrates into ground water sources. The act of managing the activities around the watershed is the Integrated Watershed Management while considering the social, economic, and environmental issues, as well as community interests to manage water resources sustainably. These watersheds, river basins, and groundwater resources provide important services for communities and biodiversity. This paper reveals that the best way to protect groundwater resources is on a watershed basis using IWM. This technique enables us to handle a variety of concerns and objectives while also allowing us to plan in a complicated and uncertain environment. IWM involves cooperation and participation from a wide range of community interests and water users, including municipalities, companies, people, agencies, and landowners, for stakeholders' input to be successful. All of the strategies and plans are produced concerning one another, as well as the overall conditions of the watershed, local land uses, and specific issues.

Increasing demand for food production with limited available water resources pose the threat to agricultural activities. The conjunctive allocation of water resources maximizes the net benefit of farmers efficiently. In this study, a novel hybrid optimization model was developed based on a genetic algorithm (GA), bacterial foraging optimization (BFO) and ant colony optimization (ACO) to maximize the net benefit of water deficit Sathanur reservoir command. The GA-based opti-mization model considered crop-related physical and economical parameters to derive optimal cropping patterns for three different conjunctive use policies and further allocation of surface and groundwater for different crops are enhanced with the BFO. The allocation of surface and groundwater for the head, middle and tail reach obtained from BFO is considered as input to ACO as a guiding mechanism to attain an optimal cropping pattern. Comparing the average produc-tivity values Policy 3 (3.665 Rs/m3) has better values relating to Policy 1 (3.662 Rs/m3) and Policy 2 (3.440 Rs/m3). Thus, the developed novel hybrid optimization model (GA-BFO-ACO) is very promising to enhance the farmer's net income as well as for the command area water conservation and can be replicated in other irrigated regions of the globe to overcome chronic land and water problems.

Water resources are threatened nowadays by pollution that comes from domestic, industrial and agricultural discharges without prior treatment. This pollution causes the degradation of water quality. Surface pollutants can seep through the soil into water tables. The objective of our work is to assess and control the physicochemical quality of the Chari Baguirmi groundwater, to protect human health. The quality of 83 boreholes was assessed, while performing analysis for 12 physicochemical parameters at the National Water Laboratory and at the Center for Quality Control of Foodstuffs in Chad. These parameters are: pH, EC, Ca2+, Mg2+, Na+, K+, Cl-, SO42-, NH4+ and NO3- , Fe2+ and HCO3-. Also, the results obtained were compared with WHO standards. The geochemical statistical approach has made it possible to characterize the hydro geochemical properties and to understand the major processes of the mineralization of groundwater resources in Chari Baguirmi region in Chad. Some of its waters are acidic and weakly mineralized, rich in Fe2+ and NH4+. The origin of the mineralization is due to the alteration of the host rocks and to the hydrolysis of silicate and ferromagnesian minerals as well as anthropogenic pollution. The ammonium concentrations in N’Djamena boreholes are higher than WHO standards, indicating the presence of pollution which may come from organic waste. These results constitute a preliminary step in understanding hydro geochemical functioning and a basis for monitoring the physicochemical quality of the water in the study area.

Uranium isotopes actively investigated as mechanistic or time scale tracers of natural processes. This paper describes the occurrence and redistribution of U in the Vendian aquifer of the paleo valley at NW Russia. Forty-four rock samples were collected from boreholes, and twenty-five groundwater samples. The U, Fe concentration, and 234U/238U activity ratio were determined in the samples. We estimated the 14C and 234U-238U residence time of groundwater in an aquifer. It has been established that the processes of chemical weathering of Vendian deposits led to the formation of a strong oxidation zone, developed above -250 m.a.s.l. The inverse correlation between the concentrations of uranium and iron is a result of removal of U from paleo valley slopes in oxidizing conditions and accumulation of U at the bottom of the paleo valley in reducing conditions, and accumulation of Fe on the slopes and removal from bottom. Almost all U on the slopes replaced by a newly formed hydrogenic U with a higher 234U/238U activity ratio. After that dissolution and desorption of hydrogenic U was occurred from the slopes during periods without any glaciations and marine transgressions. Elevated concentrations of U preserved in not oxidized lenses at the paleo valley bottom.

The fuel cell particularly the Proton Exchange Membrane Fuel Cell (PEMFC) is a new energy technology that plays a critical role in achieving market viability. The PEMFC has high power density, zero CO₂ emissions, and high conversion efficiency. However, with uniform distribution of fuel in PEMFC, we can improve the performance and reduce the cost. The PEMFC will be more efficient and effective in terms of renewable energy as a byproduct only water. Metal foam is used as an alternative for the channels in PEMFC. The model of PEMFC was established by using the ANSYS Fluent 3D Model. Then we proposed four configurations of PEMFC. The outcome demonstrates that Case IV provided outstanding performance if it is compared with the other three cases. In terms of power density, Case IV provided a high power density that is double that of Case I. The porosity of metal foam was investigated. The 0.6 porosity value is found as the optimal value. The uniform distribution of the fuel can be achieved at this value which leads to the outstanding current density.

The catastrophic failure of two dams in Libya in the night of 10th and 11th September 2023, resulted in a significant amount of water and debris destroying a large part of the city of Derna, which is located downstream of the two dams. The flood caused more than 6000 fatalities and the dis-placement of thousands of people from the city. The dams failed due to heavy rainfall caused by the Medicane Daniel, resulting in intense precipitation and the dams overspilling after reaching full capacity. This paper analyses the consequences of the dam breach by modelling the flow discharge and the flooding of the city of Derna. The analysis compares the computed quantities with the findings of the post-event satellite image analysis from UNOSAT and Copernicus, the field reports, and information gathered from the social media through AI detection. The results allows to better understand the dynamics of the dam breach, its initial parameters and an assessment of the accu-racy of the results.

Gene editing is now easy to make new disease models through in-vivo and in vitro tests. It can potentially be used to make animals with single-gene or multiple-gene changes. The mutant strains with changed germlines are no longer needed with in vivo gene editing, which uses the CRISPR-Cas9 system to target cells of interest in their normal tissues. Whereas, the AAVs and other viral vectors have made it possible to change cells selectively. Gene editing hade made it possible to use human induced pluripotent stem cells (iPSC) to model diseases that run in families. Researchers can compare and contrast the human genomes of many different ethnic and racial groups using this method. Scientists may be able to make a disease in a lab dish using iPSCs from a patient. Using CRISPR, iPSCs made from patient cells can be fixed if they have certain problems. This shows that gene therapy is possible and shows what happens when cells aren't working right. The fact that CRISPR-Cas9 can change the DNA by just one nucleotide has had a huge effect on biological studies. CRISPR is becoming more and more popular, which shows how useful, easy, and effective it is. With the broad use of CRISPR-based apps, the tool is now used for much more than just changing genes. This method can be used to screen the whole genome, control the translation of genes based on their sequence, and edit several genes at the same time. Scientists can now model diseases in different species and learn more about how genes work because of these advances. Genome-wide association studies and genome-editing tools like CRISPR are giving us a good look at the future of personalized medicine.

Neural-objective and image optimization approaches for drilling fluid rheology automation are crucial for drilling engineering optimization. A myriad of intelligent computational models are employed to predict and monitor the parameters of mud rheology and filter cake permeability posture using an artificial neural network feedforward (ANN-FF) function, a non-ANN-FF function, an image processing tool, and a model optimization tool. 498 datasets of synthetic-based mud (SBM) flat rheology from a drilling mud laboratory at Nazarbayev University were imported into a user-friendly MATLAB application using image processing and nftool. Apart from the Google TensorFlow Sequential API DNN architecture used, a Levenberg-Marquardt training algorithm with input sigmoid hidden neurons 10, 12, and 18 coupled with a linear output layer was also used to predict the SBM flow index. OBM and SBM filter cakes were processed for void spaces; however, a model study was extrapolated to maximize filtration volume Vf. The study’s findings show that the ANN-FF model employed for rheological property monitoring and prediction had higher steady and exponential levels of accuracy and a correlation coefficient of 0.96-0.99. More so, SBM and OBM image processing presented an area of void spaces of 1790M2 and 1739M2, respectively. The porosity and permeability postures of both SBM and OBM resulted in a significant void space capable of maximizing the flow index. In addition, the single-objective modelling based on a genetic algorithm did validate the experimental rheological data for flow index or filtration volume Vf optimization; the study resulted in the finding that the constrained physics-informed objective function hindered maximizing oil recovery and instead predicted possible formation damage. It is empirical to note that automating flow predictions with neural, objective, and image functions has presented an alternative novel method for non-programmers using MATLAB and Google Colabs that is capable of enhancing mud rheological parameters, drilling efficiency, and hydrocarbon recovery.

Marketing is the manner of how to make our sales the best in the market, our prices the most accessible, our clients satisfactory, and thus our brand is the largest distributed. This needs sophisticated and advanced understanding of the total network related. Indeed, marketing data may be seen in different forms such as qualitative and quantitative. However, in the literature, it is easily noticed that large bibliography may be collected about qualitative studies, against few studies on the quantitative point of view. This is a major drawback that makes the marketing science still focusing on the design, although the market is strongly depending on quantities such as money and time. Indeed, marketing data may be a time series such as brand sales per specified periods, brand related-prices over specified periods, market shares, ..., etc. The purpose of the present work is to investigate some marketing models based on time series due to brands. We will precisely study the effect of the time scale on the persistence of brands sales in the market and on the forecasting of such a persistence according to the characteristics of the brand and the related market competition or competitors. Our study is acted on a sample of Saudi brands during the period November 22, 2017 to December 30, 2021.

Microbes do not live in isolation but in microbial communities. The relevance of microbial communities is increasing due to the awareness about their biotechnological influences in a huge number of environmental, health and industrial processes. Hence, being able to control and engineer the output of both natural and synthetic communities would be of great interest. However, most of the available methods and biotechnological applications (both in vivo and in silico) have been developed in the context of isolated microbes. In vivo microbial consortia development, i.e. to reproduce the community life conditions in the wet-lab, is extremely difficult and expensive requiring of computational approaches to advance knowledge about microbial communities, mainly with descriptive modelling, and further with engineering modelling. In this review we provide a detailed compilation of available examples of engineered microbial communities as a launch pad for an exhaustive and historical revision of those computational methods devoted so far toward the better understanding, and rational engineering of natural and synthetic microbial communities.

Laser scanning is an effective tool for acquiring geometric attributes of trees and vegetation, which lays a solid foundation for 3-dimensional tree modelling. Existing studies on tree modelling from laser scanning data are vast. Nevertheless, some works don’t ensure sufficient modelling accuracy, while some other works are mainly rule-based and therefore highly depend on user inputs. In this paper, we propose a novel method to accurately and automatically reconstruct tree branches from laser scans. We first extract an initial tree skeleton from the input tree point cloud, then simplify the skeleton through iteratively removing redundant components. A global-optimization approach is performed to fit a sequence of cylinders to approximate the geometry of the tree branches. Experiments on various types of trees from different data sources demonstrate the effectiveness and robustness of our method. The resulted tree models can be further applied in the precise estimation of tree attributes, urban landscape visualization, etc.

Selected by in vitro techniques (SELEX, cell-SELEX), aptamers are strands of DNA or RNA molecules able to bind a wide range of targets, from small molecules to live cells, and even tissues, with high affinity and specificity. Due to their efficient targeting ability, aptamers are extensively used in different fields of applications. For example, they ensure high performance as cancer-related markers or in recognizing cancer cells. Actually, they represent a promising way for early diagnosis (biosensors) and to deliver imaging agents and drugs, in both cancer imaging and therapy (therapeutic aptamers). Aptamer-based biosensors (aptasensors) have attracted particular attention over the last decades, so as the possibility of using aptamers in disease therapy in substitution of monoclonal antibodies. The paper briefly reviews the most recent literature on this topic, both concerning the advances in biomedical applications and in the development of electrical aptasensors. The investigation concerning the bioelectronics features of aptamers, to be implemented in the development of electrical nanobiosensors, is also reviewed. To this aim, some recent results of a theoretical/computational framework for modelling the electrical properties of biomolecules (Proteotronics) are reported.

Senegal central regions face rainfall deficit combined with scarcity of surface water and poor quality. Populations use groundwater for drinking and irrigation. A Groundwater assessment studiebased on 42 samples aims to determine their quality. Several parameters (TDS, TH, WQI, SAR, RSC, %N, PI, KR and MR) and ion chemistry determined . Samples exhibit an alcaline pH (7.6) and hydrochemical facies mainly Ca-Na-Mg-HCO3. The ionic dominance is Na+ ˃ Ca2+ ˃ Mg2+ ˃ K+ and HCO3- ˃ Cl- ˃ SO42- ˃ NO3- ˃ F-. From TDS and WQI index most of the groundwaters are suitable for drinking. Irrigation quality (based on SAR, %N, RSC, KR, MR) varie from excellent to good water type. Plotting chemical data (USSL salinity & Wilcox diagrams) reveals that the majority of the groundwater samples belong to the fields excellent to good and from good to permissible . Natural processes (rock weathering, mineral dissolution, evaporation and ion exchange) control groundwater quality. As the region faced a persistent rainfall deficit combine with fragile groundwater quality should alert the stakeholders. A sustainable development of the region can be faced if strong measures are planned to follow water quality evolution and quantity available for human purposes

Agricultural activities profoundly affect groundwater levels in Saudi Arabia. The Al Kharj and Wadi Sahba areas, central Saudi Arabia, produce groundwater mainly from the Jurassic Arab/Jubaila aquifer and the overlying Cretaceous Biyadh aquifer. A geographic information system analysis and linear regression analyses show that from 1978 to 2016, significant agricultural overexploitation of the area’s fossil groundwater was associated with groundwater level drops of ~104 m in Al Kharj and ~48 m in Wadi Sahba. The estimated total volume of groundwater withdrawal across both aquifers during this period of wheat and alfalfa irrigation was ~27 billion m3. Landsat image analysis shows that agricultural land use decreased by ~66% over the same period due to overexploitation. The 2016 phase-out of alfalfa farming was associated with increases in groundwater levels: ~26 m in the Arab/Jubaila aquifer and ~3 m in the Biyadh aquifer. This recovery was likely due to lateral flow from surrounding fossil water within the aquifer given the absence of significant surface recharge. Model-based evaluation of surface recharge of the aquifer reveals very low potential for surface infiltration, with almost no recharge into the deep aquifer. Assuming that recovery continues at the present rate, the average groundwater level for the Arab/Jubaila aquifer is expected to reach 98 m below ground level in 2025 and 74 m below ground level in 2030.

With the gradual improvement of coal mining efficiency, the disturbance of groundwater system caused by the high-intensity mining mode also increases, which is a more severe challenge to the prevention of mine safety and the protection of water resources in mining areas. How to accurately describe the dynamic changes of the groundwater system under mining and quantitatively predict mine water inflow is a major problem in the current research. Based on the full analysis of the response characteristics of groundwater system to the extraction disturbance, this paper forms a kind of method to establish a mine hydrogeological conceptual model that can accurately represent the water inrush process, and uses the MODFLOW non-structural division grid to accurately characterize the formation structure, and finally make accurate water inflow prediction. Taking the Caojiatan Coal Mine in Shaanxi Province, China as an example, a numerical model of unstructured mine water inrush was established for the first time, and the changes of water inflow source and water inflow intensity were quantitatively evaluated. Compared with the traditional water inflow prediction method, it is found that the prediction accuracy is improved by 12%~17% by detailing the response characteristics of complex groundwater system under high-strength coal seam mining conditions. The method is of great significance and promotion value for the comprehensive understanding of the disturbance characteristics of human underground engineering activities, such as coal mining, on the groundwater system, and for accurately predicting water inflow.

Data-driven models based on artificial intelligence are efficiently used to solve complex problems. The quality of groundwater is of utmost importance, as it directly impacts human health and the environment. In major parts of the world groundwater is the main source of drinking water, it is essential to periodically monitor water quality. Conventional water quality monitoring techniques involve periodical collection of water samples and analysis in the laboratory. This process is expensive, time consuming and involves lot of manual labor. The aim of our study is to build an ant colony optimized neural network for predicting groundwater quality parameters. We have proposed artificial neural network comprising of six hidden layers. The approach was validated using our groundwater quality dataset of a hard rock region in the northern part of Karnataka, India. Groundwater samples were collected by us periodically from March 2014 to October 2020 from 50 wells in this region. These samples where analysed for measuring the pH, Electrical Conductivity, Na+, Ca+, Na+, K+, Mg2+, F-, Cl- and U+. The temporal dataset was split for training, testing and validation of our model. Metrics such as R2 (Coefficient of Determination), RMSE (Root Mean Squared Error), NSE (Nash–Sutcliffe efficiencies) and MAE (Mean Absolute Error) were used to evaluate the prediction error and model performance. These performance evaluation metrics indicated the efficiency of our model in predicting the temporal variation in groundwater quality parameters. The method proposed by us can be used for prediction and the temporal frequency of sample collection can be reduced to save time and cost. The results also confirm that the combination of artificial neural network with ACO is a promising tool to optimize weights while training the network, and hence will help in reasonable prediction of groundwater quality parameters.

Groundwater is the most extracted raw material in the world with global annual withdrawal rates of 800–1500 km3/year. In East and Southern Africa, 70 % of the population are reliant on shallow groundwater as their primary drinking water source. With increased population growth, intensification of agriculture and industrialization, conflicting demands on groundwater present a challenge to achieve the Sustainable Development Goals (6,3,11,12,15). Between 2015 and 2018, the Horn of Africa was affected by a series of climatic induced events, namely El Nino, La Nina and the Indian Ocean Diopole. These events modified the variability of rainfall patterns and resulted in long periods of low rainfall, low recharge and high evapotranspiration. As a result, shallow aquifers in alluvial deposits of Somali region have low yields and produce brackish and saline water. That situation prompted humanitarian water professionals to finance the transportation of water from selected locations with high groundwater potential through water trucks to areas facing groundwater depletion and drought. To address this challenge, UNICEF explored alternative, sustainable deeper groundwater sources that could be extracted using solar water pumping technology for multi water use. This paper describes a three-phase methodology of deep groundwater development of wells in the Ogaden Jesoma sandstone aquifers of the Somali region of the Horn of Africa to a depth of 600 meters below ground level. The results concluded that the deep sandstone aquifer of Jesoma can provide fresh water with yields of 15 l/s to the local population of Somali region. to the study provided insights into deep groundwater identification and development as well as adaptive deep boreholes drilling as a source for climate resilient water supplies.

Animal models of diseases in particular, the mice, are considered to be the cornerstone for translational research in immunology. The aim of the present study is to model the geometry and analyze the network structure of murine lymphatic system (LS). The algorithm for building the graph model of the LS makes use of anatomical data. To identify the edge directions of the graph model, a mass balance approach to lymph dynamics based on Hagen-Poiseuille equation is applied. It is the first study in which a geometric model of the murine LS has been developed and characterized in terms of its structural organization and the lymph transfer function. Our study meets the demand for quantitative mechanistic approaches in the growing field of immunoengineering to utilize or exploit the lymphatic system for immunotherapy.

It is shown by numerical modelling that anisotropic diffusion can compensate and even overcome diffusion broadening - the main limiting factor of devices working at atmospheric pressure. The thickness of ion clouds coming out of the ionisation chamber is reduced ~ 1000 times in the ADMA inlet increasing the resolution. This finding has a great potential that enables construction of a device with resolution close to that of currently available desktop ion separation devices – high pressure mass spectrometers, but with much lower cost of manufacture and with smaller dimensions. Comprehensive numerical modelling along with mathematical analysis of physical concepts enables reduction of the footprint and manufacturing costs. Modelling determined that the resolving power (RP) potential of the ADMA is greater than the RP of currently available on the market devices for the airport security market. The ADMA technology enables very fast detection of threats; at least 100 times faster than currently used in Ion Mobility Spectrometers (IMS). This potentially allows an increase in passenger throughput in airports.

A set of programs for the numerical simulation of the diffusion decomposition processes was developed by using simulation methods, kinetic and particle method. The complex has been validated on the model system Ni-Al by the growth of -phase separations. The results on the evolution of the distribution function and other characteristics of the ensemble, which in the zero volume fraction approximation are asymptotically in good agreement with the theory and the experiment, have been obtained. The peculiarity of the created program complex is the possibility of its adaptation to the description of the decomposition of multicomponent multiphase systems. Fig. 6, list of references - 19 titles.

Resilience has emerged as a buzzword among researchers and practitioners. However, despite its popularity, there has been little progress in moving it from an elaborate metaphor describing an idyllic state of the system to a tool for planning and managing adaptation. While case study research is rich with examples of systems that have proven to be resilient or are striving to develop resilience, there is no defined approach that operationalises concepts described in the literature into the planning process. This paper helps close this gap by illustrating how facilitated modelling can be used for resilience planning in socio-ecological systems. The paper summarizes our experience using facilitated system dynamics to inform a model-based discussion of food security resilience to climate change in Guatemala. We identify at least three positive outcomes from the intervention, which a) helped to build consensus about the meaning of resilience, b) improved stakeholders understanding of adaptation and c) outlined potential policies to enhance resilience.

It is the aim of this article to introduce a concise notation that is be able to capture the most important dimensions of sexuality and thus facilitate discussions. Moreover, the major three dimensions - sex, gender, and sexual orientation - lead to a straightforward classification which motivates the quest for stringent explanatory models, some of which are also discussed.

. This paper features an analysis of the relative effectiveness of a variety of methods of modelling Realised Volatility (RV), namely: the use of Gegenbaur processes in Auto-Regressive Moving Average format, GARMA, as opposed to Heterogenous Auto-Regressive HAR models and simple rules of thumb. The analysis is applied to two data sets that feature the RV of the S&P500 index, as sampled at 5 minute intervals, provided by the Oxford Man RV database. The GARMA model does perform slightly better than the HAR model, but both models are matched by a simple rule of thumb regression model based on the application of lags of squared, cubed and quartic, demeaned daily returns.