Water

Urban stormwater has become a persistent concern on a global scale due to its adverse environmental implications. It is the prime vector of aquatic contaminants worldwide that causes pollutants when water bodies drain. Bioretention systems are increasingly used to alleviate setbacks associated with stormwater run-off in urban locales. It has played a substantial role in the implementation of low impact development (LID), a concept that addresses urban stormwater problems caused by land changes and development. The use of LID technologies is an innovative approach. However, it is beset with challenges, such as the insufficiency of data on rainfall distribution and difficulty in interpreting data. To address these research gaps, the present study developed a fuzzy rough set data algorithm for bioretention systems. Event mean concentration calculations and fuzzification of rainfall were performed to produce a rough set-based decision rule. Using the Weibull probability distribution, fuzzification of rainfall and parameter data, rule induction, and Preece testing, bioretention design considerations were determined. The bioretention characterizations generated evident pollutants present in the catch basin before and after filtration. In addition, the bioretention characterization conducted in this study was able to reduce the number of tests needed for rainfall identification based on the different attributes. Full article

The interaction of bedform and vegetation cover significantly affects the turbulent flow parameters. To investigate this interaction, experiments were carried out in both a gravel-bed river and a laboratory flume. The purpose of field investigations was to find the slopes for both the entrance section and exit section of pools, the grain size of the bed material, and the flow condition. Based on field data, without considering any scaling analysis, a straight pool was constructed in a laboratory flume that was 0.9 m wide, 0.6 m deep, and 14 m long. The entry and exit slopes of the straight pool were 7.4° and 4°, respectively. The straight pool had vertical side walls and a gravel bed with a median grain size of d₅₀ = 23.3 mm. Plastic cylinders planted in an irregular pattern in the channel beds were used to model rigid submerged vegetation. The velocity components were recorded by using an ADV at 200 Hz. In this study, the distributions of velocity, Reynolds stress, and TKE were investigated for flows in the presence of submerged rigid vegetation in channel beds with various area densities of vegetation. Results show that the shape of Reynolds stress distribution depends on the entrance and exit slopes of the pool, as well as the irregular distribution pattern of vegetated elements. Inside the pool with the presence of submerged vegetation in the channel bed, the maximum TKE appears above the bed surface with a larger distance depending on the area density of vegetation in the channel bed. However, the momentum exchange and turbulent energy are likely influenced by the secondary circulation of the flows associated with the irregular distribution of vegetated elements in the channel bed. Results of the quadrant analysis show that the momentum between the flow, bedform, and vegetated elements is mostly transferred by sweep and ejection events. The outward event tends to grow toward the water surface, reaching the highest amount near the water surface. At the pool entrance section where the flow is decelerating, the ejection event is dominant near the bed while the sweep event is strong near the water surface. With the decrease in the vegetation density in the pool bed, both the ejection and outward events become dominant. Full article

Tanneries produce large amounts of wastewater with high concentrations of suspended solids, organic matter, and salts. Treatment and reuse of these effluents are of great importance to preserve water resources and save costs. Although suspended solids and high percentages of organic matter can be eliminated by physico-chemical and biological processes, refractory chemical oxygen demand (COD) and salts will remain in the wastewater after these processes. In particular, chloride and sulphate ion concentrations may hinder the treated wastewater from being reused or even discharged according to legal standards. In this work, two nanofiltration membranes and two reverse osmosis membranes are tested to assess these technologies as regeneration processes for biologically treated tannery wastewater. Permeate flux and rejection of organic matter and ions were measured at different operating conditions (transmembrane pressure and cross-flow velocities) at both total recycle and concentration modes. Results showed that the difference between permeate fluxes of nanofiltration (NF) membranes and reverse osmosis (RO) membranes was very high. Thus, at 20 bar and 1.77 m·s⁻¹, the permeate flux of the two tested NF membranes in the total recycle mode experiments were 106 and 67 L·m⁻²·h⁻¹, while the obtained permeate fluxes for the RO membranes were 25 and 18 L·m⁻²·h⁻¹. Concerning rejections, RO membranes rejected almost 100% of the salts, whereas NF membranes reduced their rejection when faced with increasing concentration factors (salt rejection between 50–60% at the highest concentration factor). In addition, the fouling of RO membranes was lower than that of NF membranes, recovering more than 90% of initial permeability by only water rinsing. In contrast, chemical cleaning was necessary to increase the permeability recovery of the NF membranes above 90%. The considerably lower rejections and the higher membrane fouling of the NF membranes lead us to conclude that reverse osmosis could be the most feasible technique for water reuse in the tannery industry, though the permeate fluxes are lower than those achieved with NF membranes. Full article

Local scour around submerged piles in currents are common in coastal and offshore engineering. This paper studies the influences of the submergence ratio (flow depth to pile height) on local scour around a square pile in steady flow. Submergence ratio ranging from 1–4, as well as two unsubmerged tests, were tested with a 10 × 10 square pile of 20 cm height. The three-dimensional profiles were measured to study the scour and deposition characteristics. Results show that the maximum scour depth was always at the upstream corner points rather than at the symmetry center point of the pile. The temporal maximum scour depth achieved its equilibrium sate in less than 4 h for each test. The equilibrium scour depths at the upstream corner points were independent of the submergence ratio when the latter was larger than 1.5. These findings give meaningful reference to the numerical simulations and local scour depth protections in the submerged pile cases deeper than which the flow depth does not affect the equilibrium scour depth. Full article

Precipitation elasticity provides a basic estimate of the sensitivity of long-term streamflow to changes in long-term precipitation, and it is especially useful as the first assessment of climate change impact in land and water resource projects. This study estimated and compared the precipitation elasticity (ε_p) of streamflow in 86 catchments within Pakistan over 50 major rivers using three widely used analytical models: bivariate nonparametric (NP) estimator, multivariate NP analysis, and multivariate double logarithm (DL) model. All the three models gave similar values of elasticity in the range of 0.1–3.5 for over 70–75% of the catchments. This signifies that a 1% change in the annual mean precipitation compared to the long-term historic mean annual precipitation will amplify the streamflow by 0.1–3.5%. In addition, the results suggested that elasticity estimation of streamflow sensitivity using the multivariate DL model is more reliable and realistic. Precipitation elasticity of streamflow is observed high at altitudes ranging between 250 m and 1000 m while the longitudinal and latitudinal pattern of ε_p shows higher values in the range of 70–75 and 32–36 decimal degrees, respectively. The ε_p values were found to have a direct relationship with the mean annual precipitation and an inverse relationship with the catchment areas. Likewise, high ε_p values were noticed in areas where the mean annual temperature ranges between 15 and 24 °C. Full article

The formation of algal and cyanobacterial blooms caused by the eutrophication of water bodies is a growing global concern. To examine the impact of extreme weather events on blooms, eutrophication-related parameters (e.g., water temperature, nitrate, ammonium, nitrite, and soluble reactive phosphate (SRP)) were quantitatively assessed monthly over three years (2017–2019) at Lake Seeburg (Central Germany), a shallow eutrophic lake with regular cyanobacterial blooms. In addition, SRP concentrations in sediment pore water were assessed monthly for one year (2018). The monitoring period included a three-day extremely heavy rain event in 2017 as well as a severe drought in summer 2018. No such extreme weather conditions occurred in 2019. After the heavy rain event in 2017, anoxic water containing high levels of ammonium and SRP entered the lake from flooded upstream wetlands. This external nutrient spike resulted in a heavy but short (3 weeks) and monospecific cyanobacterial bloom. A different situation occurred during the exceptionally hot and dry summer of 2018. Especially favored by high water temperatures, SRP concentrations in sediment pore waters gradually increased to extreme levels (34.4 mg/L). This resulted in a strong and sustained internal SRP delivery into the water column (69 mg/m²·d⁻¹), which supported the longest-lasting cyanobacterial bloom (3 months) within the three-year monitoring period. Subsequent biomass decay led to oxygen-depleted conditions in the bottom waters, elevated ammonium, and, later, nitrate concentrations. Our observations demonstrate the particular effects of extreme weather events on nutrient dynamics and the phytoplankton composition in the lake. As the frequency and intensity of such events will likely increase due to climate change, their impacts need to be increasingly considered, e.g., in future remediation strategies. Full article

Sensitive detection with cell biosensors requires optimization of their working conditions and standardization of the response in variable physicochemical conditions. The introduction of an analyte to a sensor, which contributes to this variability, may account for the modeling of microbial metabolism. We constructed a multiparameter model of a water toxicity sensor of Automatic Biodetector for Water Toxicity (ABTOW), developed by our group and based on nitrifying bacteria. The model describes the kinetics of nitrification as a function of four orthogonal parameters: temperature, pH, oxygen and ammonium concentration. Furthermore, we characterized the signal-to-noise ratio (SNR) of the ABTOW readout as a function of these parameters. Thus, a region of parameter space corresponding to optimal ABTOW operation is identified and its sensitivity quantified. We applied the model to describe the ABTOW performance in non-equilibrium conditions produced by rapid changes in pH and temperature. In sum, the model based on four physicochemical parameters describes changes in the biosensor's activity, the biological element of which are nitrifying bacteria characterized by simple chemolithoautotrophic metabolism. The description of reaction kinetics through multiparameter modeling in combination with stability analysis can find application in process control in biotechnology, biodetection and environmental research. Full article

Advances in machine-learning techniques can serve practical water management needs such as salinity level estimation. This study explores machine learning, particularly deep-learning techniques in developing computer emulators for a commonly used process model, the Delta Simulation Model II (DSM2), used for salinity estimation in California’s Sacramento-San Joaquin Delta (Delta). We apply historical daily input data to DSM2 and corresponding salinity simulations at 28 study locations from 1990 to 2019 to train two machine-learning models: a multi-layer perceptron (MLP) and Long-Short-Term Memory (LSTM) networks in a multi-task learning framework. We assess sensitivity of both networks to the amount of antecedent input information (memory) and training data to determine appropriate memory size and training data length. We evaluate network performance according to several statistical metrics as well as visual inspection. The study further investigates two additional networks, the Gated Recurrent Unit (GRU) and Residual Network (ResNet) in salinity modeling, and compares their efficacy against MLP and LSTM. Our results demonstrate strong performance of the four neural network models over the study period, achieving absolute bias below 4%, plus near-perfect correlation coefficients and Nash–Sutcliffe efficiency coefficients. The high complexity LSTM shows slight performance edge. We further show that deeper and wider versions of MLP and LSTM yield only marginal benefit over their baseline counterparts. We also examined issues related to potential overfitting by the proposed models, training data selection strategies, and analytical and practical implications. Overall, this new study indicates that machine-learning-based emulators can efficiently emulate DSM2 in salinity simulation. They exhibit strong potential to supplement DSM2 in salinity modeling and help guide water resource planning and management practices for the Delta region. Full article

Water management for natural channels is a frequent challenge due to the inefficient usage of water resources. The 2030 Agenda of the United Nations (SDG 6 of sustainable development) focuses its attention on water and sanitation. The Sara Guerrero site, located in the Mocache municipality in Los Ríos province (Ecuador), has issues related to access to drinking water, flood control, and crop irrigation that affect 4300 people and 24,000 hectares. The river overflows throughout the rainy season (late December to early May), whereas there is a noticeable water shortage during the dry season. This project aims to design a multiple-use earth dam on the Vinces River, simulating the resulting flow in extreme cases due to its possible failure. Such a study implies the development of a contingency plan for the preservation of life. It considers (i) dam breach analysis and design, and (ii) hydraulic model development using the ArcMap and HEC-RAS software packages. The design includes a waterproofing system that controls possible leaks and a cymbal spillway, mainly for raw water collection. The generated model showed that the shorter the failure time, the higher the maximum output flow. Modelling revealed that four towns would be affected for a maximum of 31 h in extreme cases. This approach offers comprehensive management for this community with regards to the earth dam and flood control. Full article

Recently, ClO₂-based oxidation has attracted increasing attention to micropollutant abatement, due to high oxidation potential, low disinfection byproduct (DBPs) formation, and easy technical implementation. However, the kinetics, reactive sites, activation methods, and degradation pathways involved are not fully understood. Therefore, we reviewed current literature on ClO₂-based oxidation in micropollutant abatement. In direct ClO₂ oxidation, the reactions of micropollutants with ClO₂ followed second-order reaction kinetics (k_app = 10⁻³–10⁶ M⁻¹ s⁻¹ at neutral pH). The k_app depends significantly on the molecular structures of the micropollutant and solution pH. The reactive sites of micropollutants start with certain functional groups with the highest electron densities including piperazine, sulfonyl amido, amino, aniline, pyrazolone, phenol groups, urea group, etc. The one-electron transfer was the dominant micropollutant degradation pathway, followed by indirect oxidation by superoxide anion radical (O₂^•−) or hydroxyl radical (^•OH). In UV-activated ClO₂ oxidation, the reactions of micropollutants followed the pseudo-first-order reaction kinetics with the rates of 1.3 × 10⁻⁴–12.9 s⁻¹ at pH 7.0. Their degradation pathways include direct ClO₂ oxidation, direct UV photolysis, ozonation, ^•OH-involved reaction, and reactive chlorine species (RCS)-involved reaction. Finally, we identified the research gaps and provided recommendations for further research. Therefore, this review gives a critical evaluation of ClO₂-based oxidation in micropollutant abatement, and provides recommendations for further research. Full article

The aim of the study was to investigate the utility of artificial neural networks (ANNs) for the estimation of reference evapotranspiration (ETo) on the Peloponnese Peninsula in Greece for two representative months of wintertime and summertime during 2016–2019 and to test if using fewer inputs could lead to satisfactory predictions. Datasets from sixty-two meteorological stations were employed. The available inputs were mean temperature (Tmean), sunshine (N), solar radiation (Rs), net radiation (Rn), vapour pressure deficit (es-ea), wind speed (u₂) and altitude (Z). Nineteen Multi-layer Perceptron (MLP) and Radial Basis Function (RBF) models were tested and compared against the corresponding FAO-56 Penman Monteith (FAO PM) estimates of a previous study, via statistical indices. The MLP1 7-2 model with all the variables as inputs outperformed the rest of the models (RMSE = 0.290 mm d⁻¹, R² = 98%). The results indicate that even ANNs with simple architecture can be very good predictive models of ETo for the Peloponnese, based on the literature standards. The MLP1 model determined Tmean, followed by u_2, as the two most influential factors for ETo. Moreover, when one input was used (Tmean, Rn), RBFs slightly outperformed MLPs (RMSE < 0.385 mm d⁻¹, R² ≥ 96%), which means that even a sole-input ANN resulted in satisfactory predictions of ETo. Full article

A new method of searching for periodicity has been developed on the basis of extensive spatio-temporal data. The result, however, produces little more than doubts. The standard Fourier analysis indicates some periods, namely 3.7-, 7.0-, 8.8-, and 17.5-year periods, and these periodic signals are distributed relatively consistently over some regions of Europe. However, the expectations that the exact harmonic 8.8 years of 17.5 years, and not so exact 3.7 years of 7.0 years will be present at the same or close stations are not fulfilled. Full article

The coffee processing industry produces toxic and low biodegradable effluent, which can pollute water bodies. A pre-treatment study on coffee effluent using a dual-media biofilm reactor (DM-BR) containing sand and Hexafilter (HEX) was conducted alongside a control biofilm reactor (C-BR) containing sand media. The novelty of this study lies in the use of dual media in biofilm reactor (DM-BR) for real coffee effluent treatment, where these processes were used individually in previous studies. The performance of DM-BR and C-BR in treating coffee effluent were investigated at different hydraulic retention times (HRTs), 24, 48 and 72 h, and the degrading bacteria were identified. Both biofilm reactors were inoculated with a recycled paper mill-activated sludge and acclimatised for 97 days. The DM-BR displayed the highest removal of chemical oxygen demand (COD) and NH₄⁺-N at 47% and 38%, respectively, within 48 h of HRT, whereas colour and tannin–lignin reached maximum average removal of 21% and 29%, respectively, at 24 h of HRT. The combination of sand and HEX media in a system showed COD and NH₄⁺-N removal improvement at 48 h of HRT and encouraged a variety of bacterial species growth. Bacterial characterisation analysis revealed Proteobacteria to be dominant. Full article

Numerous questions and problems on Earth and questions with respect to other planets arise from morphodynamic processes caused by sediment movements driven by flows of fluids, such as water, air and other gases. A sediment surface opposes the current with a resistance that is determined by its skin or grain roughness. As soon as sand waves, such as ripples and/or dunes, are formed, these bedforms cause a further resistance to the flow, the so-called form roughness. Dependent on the dimensions of the ripples and dunes, the form roughness can be much more pronounced than the skin roughness. The relevant literature provides a large number of solution approaches based on different basic ideas and different result quality. The aim of this paper is a comparative analysis of solution approaches from the literature. For this purpose, 14 approaches to bedform-related friction in the subaqueous case are evaluated using 637 measurements from laboratory and natural settings. We found that all approaches were significantly more accurate for ripples than for dunes. Since this was equally the case for all approaches tested, it is reasonable to assume that this is caused by measurement inaccuracies for dunes in the natural case rather than due to the approaches themselves. The approach of Engelund 1977 proved to be most accurate among all approaches investigated here. It is based on the Borda–Carnot formulation and an additional empirical term. An analytical derivation and justification is provided for this additional term. Full article

Climate change is one of the most important problems facing society in the 21st century. Despite the uncertainty about the behaviour of rainfall due to climate change, what is clear is that average rainfall has been reduced in the inland areas and headwaters of Spain’s river basins. The Tagus basin is one of the most affected, with implications for the Jucar and Segura basins. The working hypothesis is to corroborate with the data collected on the effects of climate change on the TTS. To this end, the following methodology has been applied: (a) analysis in the headwaters of the Tagus, using data on precipitation, surface runoff and reservoir water; (b) analysis of the resources of the Segura basin (supply and demand), based on the basin organisation’s own data; (c) construction of a water balance adjusted to the Bajo Segura district (Alicante), a user of the water transferred for agricultural use. Likewise, the data provided by the basin organisation have made it possible to corroborate the data on consumption and allocation of the corresponding volumes of water. The results obtained make it possible to put forward a novel proposal in the scientific field related to hydrological planning based on the principles of sustainability. Full article

The aim of the study was to assess the groundwater quality in a rural area affected by the abandoned pyrite ash waste dumps. The abundance of major ions in groundwater depends largely on the nature of the rocks, climatic conditions, and mobility. To evaluate geochemical processes, 30 groundwater samples collected from Valea Calugareasca, Prahova County, Romania, were analyzed for the major anions (NO₃⁻, SO₄²⁻_, Cl⁻, HCO₃⁻, and F⁻) and cations (Ca^2+, Mg²⁺, Na⁺, and K⁺), which are naturally highly variable due to climatic and geographical location conditions. Ca²⁺, Na⁺, Mg²⁺, and K⁺ varied between 118 and 275 mg/L, 32 and 160 mg/L, 12.2 and 78.4 mg/L, and 0.21 and 4.48 mg/L, respectively. NO₃⁻ levels exceeding the World Health Organization (WHO) limit of 50 mg/L were identified in 17% of the groundwater samples, mainly as result of fertilizers applied to agricultural activities. The hydrogeochemical study identified dolomite dissolution and halite precipitation as natural sources of ions as well as the presence of pyrite as a source of SO₄²⁻ ions in 60% of the samples. The sulfate content varied between 125 and 262 mg/L. Bicarbonate and chloride concentrations varied between 202 and 530 mg/L and 21 and 212 mg/L. The saturation index indicates the contribution of Ca²⁺ ions in the groundwater samples came from some processes of dissolving rocks such as aragonites (values between 1.27 and 2.69) and calcites (values between 1.43 and 2.82). Negative halite values indicated that salt accumulation results from precipitation processes. Only 10% of the analyzed groundwater samples were suitable for human consumption, the samples being situated on the hill, far away from the pyrite ash waste dumps and agricultural land. Full article

The conventional drinking water treatment process involves disinfecting water at the final stage of treatment to ensure water is microbiologically safe at customer taps. Monochloramine is a popular disinfectant used in many water distribution systems (WDSs) worldwide. Understanding the factors that impact monochloramine decay in the WDS is critical for maintaining disinfection at the customer tap. While monochloramine residue moves through a WDS, it decays via several pathways including chemical, microbiological, and wall decay processes. The decay profile in these pathways is often site-specific and depends on various factors including treated water characteristics. In a water quality network model, the decay of a chemical species is often modelled using two parameters that represent bulk and wall decay kinetics. Typical bulk decay characteristics of monochloramine for a specific WDS can be easily established in the laboratory using grab sample tests, while in a real situation, wall decay is difficult to quantify. In this study, we compared two different approaches to model monochloramine decay in a WDS. In the first approach, the wall decay parameter was quantified using a parameter optimisation technique with monochloramine concentrations at different network locations simulated using a water quality network model. In the second approach, a data analytics model was developed using a machine learning algorithm. For both approaches, the model predicted monochloramine concentrations closely matched the observed data. Our study suggests that the data analytics model has a relatively higher accuracy in predicting monochloramine residual concentrations in a WDS. Full article

The COVID-19 pandemic (Coronavirus disease 2019) remains problematic in all its manifestations on the global stage where countless events of human-to-human exposure have led to fatal cases; thus, the aftermath being an unprecedented public health concern, with inaccessible health care and the instability of economies and financial institutions. These pose massive obstacles that can insatiably devour existing human resources causing negative impacts, especially in developing countries. Tracking the origin, dissemination and mutating strains of the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) on population-wide scales is a somewhat overwhelming task, with the urgent need to map the dissemination and magnitude of SARS-CoV-2 in near real-time. This review paper focuses on the poor sanitation of some waterbodies and wastewater management policies in low-income African countries, highlighting how these contribute to the COVID-19 pandemic on the continent. Since the outbreak of the novel coronavirus pandemic, there has been an upsurge in scientific literature and studies concerning SARS-CoV-2 with different opinions and findings. The current paper highlights the challenges and also summarizes the environmental aspects related to the monitoring and fate of the SARS-CoV-2 genomes in the aquatic milieu of Sub-Saharan Africa. Full article

Xinjiang, an arid region of China, has experienced a substantial warming–wetting trend over the past five decades. However, climate change has affected vegetation growth/greening in arid Central Asia in unexpected ways due to complex ecological effects. We found a significant greening trend (consistent increase in the normalized difference vegetation index or NDVI) from 1982 to 1996, during the growing season; however, the NDVI consequently decreased and plateaued from 1997 to 2015, especially in naturally vegetated regions. Atmospheric vapor pressure deficit (VPD) is a critical driver of vegetation growth, is a direct measure of atmospheric aridity, and has increased sharply in recent decades. A partial correlation analysis indicated a significant relationship between growing season NDVI and VPD from 1997 to 2015. This implies that decreased VPD corresponds to increasing NDVI, and increasing VPD corresponds to a decrease and plateauing in the NDVI trend. Using the partial derivative equation method, our results suggest that the trend in growing season NDVI was affected primarily by increasing VPD (contributing 87.57%) from 1997 to 2015, especially in the grassland and desert biomes. Rising temperatures lead to a greater VPD, resulting in exacerbated evaporative water loss. Soil drought and atmospheric aridity limit plant stomatal conductance and could effectively lead to a decrease in the greening trend and increased vegetation mortality in arid Xinjiang. Our results emphasize the importance of VPD as a limiting factor of greening trends in arid regions. The influence of VPD on vegetation growth should be considered when evaluating arid ecosystem functioning under global warming. Full article