Water, Volume 16, Issue 11 (June-1 2024) – 176 articles

The appropriate design and operation of spillways are critical for dam safety. To enhance design practices and gain insights into flow hydraulics, both experimental and numerical modeling are commonly employed. In this study, we conducted a numerical investigation of flow over a mildly sloping (1V:3H) stepped spillway with various step geometries using a multi-phase mixture model with dispersed interface tracking in ANSYS Fluent. The model was validated against experimental data from Utah State University, focusing on water surface profiles over the crest, velocities, and air concentrations. The validated numerical model was used to simulate flow over different step geometries (i.e., 0.2 m H uniform Step, 0.1 m H uniform step, non-uniform steps, adverse slope steps, and stepped pool) for a range of discharges from 0.285 m³/s/m to 1.265 m³/s/m. While flow depths over the crest and velocities in the chute compared well with experimental results, air concentrations exhibited some deviation, indicating numerical limitations of the solver. The shift in the location of the inception point was found to be mainly influenced by a higher flow rate than the different design configurations over an identical mild slope. The downstream non-linear flow velocity curve with different flow rates indicated less effectiveness of the step roughness over a high flow rate as a result of the reduction in relative roughness. The theoretical velocity ratio indicated the least reduction in downstream velocity with the stepped pooled spillway due to the formation of a “stagnant pool”. A higher negative-pressure region due to flow separation at the vertical face of the steps was obtained by adverse slope steps, which shows that the risk of cavitation is higher over the adverse slope step spillway. Turbulent kinetic energy (TKE) was found to be higher for uniform 0.2 m H steps due to the strong mixing of flow over the steps. The least TKE was found at the steps of the stepped pool spillway due to the formation of a “stagnant pool”. Uniform 0.2 m H steps achieved the maximum energy dissipation efficiency, whereas the stepped pool spillway obtained the least energy dissipation efficiency, introducing higher flow velocity at the stilling basin with a higher residual head. The adverse slope and non-uniform steps were found to be more effective than the uniform 0.1 m H steps and stepped pool spillway. The application of uniform steps of higher drop height and length could achieve higher TKE over the steps, reducing the directional flow velocity, which reduces the risk of potential damage. Full article

To deeply investigate the impact of closed coal mines on groundwater sulfate contamination in the Panlong River basin, Zaozhuang, Shandong Province, China, the hydrochemical characteristics and controlling factors of groundwater were analyzed based on 64 surface water and groundwater samples. The sources of sulfate contamination were identified by sulfur and oxygen isotope analysis. The results indicate that the sulfate content in the pore groundwater exceeds the Standard for Groundwater Quality (China) Category III (250 mg/L), with a maximum content of 666.2 mg/L. Specifically, the exceedance rate of sulfate in pore water near the western boundary of the Taozao coal field is directly related to mine water. The exceedance rate of sulfate in karst groundwater is 28%, peaking at 1131 mg/L, and is mainly distributed outside the western boundary of the Taozao coalfield and near the Dingzhuang water source in the southeast of the coalfield, indicating a significant influence from high-sulfate mine water in the coal-bearing strata. The sulfur and oxygen isotope differences are significant between surface water, mine water, karst water, and pore water. Through Bayesian end-member analysis, it was determined that 40–83% of sulfate in the downstream pore water of the Taozao coal field originated from mine water, while 48–86% of the sulfate in the karst water originated from mine water, which greatly affects the groundwater in the western and southeastern parts of the Taozao coalfield. Therefore, measures should be taken as soon as possible to control the risk of sulfate pollution of neighboring groundwater, especially karst groundwater, by mine water from closed coal mines. Full article

YOLOv5 is currently one of the mainstream algorithms for object detection. In this paper, we propose the FRL-YOLO model specifically for river floating object detection. The algorithm integrates the Fasternet block into the C3 module, conducting convolutions only on a subset of input channels to reduce computational load. Simultaneously, it effectively captures spatial features, incorporates reparameterization techniques into the feature extraction network, and introduces the RepConv design to enhance model training efficiency. To further optimize network performance, the ACON-C activation function is employed. Finally, by employing a structured non-destructive pruning approach, redundant channels in the model are trimmed, significantly reducing the model’s volume. Experimental results indicate that the algorithm achieves an average precision value (mAP) of 79.3%, a 0.4% improvement compared to yolov5s. The detection speed on the NVIDIA GeForce RTX 4070 graphics card reaches 623.5 fps/s, a 22.8% increase over yolov5s. The improved model is compressed to a volume of 2 MB, representing only 14.7% of yolov5s. Full article

Small intermountain river basins are most suitable for developing new methods to estimate water balance due to their well-defined catchment boundaries, relatively rapid runoff processes, and accessible landscapes for study. In general terms, dissecting the hydrograph of a small mountain river requires calibration of the flow model against multi-year data sets, including (a) glacier mass balance and snow water content, (b) radiation balance calculation, (c) estimation of the groundwater contribution, and (d) water discharge measurements. The minimum primary data set is limited to the precipitation and temperature distributions at the catchment. This approach postulates that the conditions for the formation of all components of river flow are known in advance. It is reduced to calculating the dynamic balance between precipitation (input part) and runoff, ablation, and evaporation (output part). In practice, accurately accounting for the inflow and outflow components of the balance, as well as the impact of regulating reservoirs, can be a challenging task that requires significant effort and expense, even for the extensively researched catchments. Our studies indicate the potential benefits of an approach based on one-time, but detailed, observations of stable isotope composition, temperature, and water chemistry, in addition to standard datasets. This paper presents the results of the 2022–2023 work conducted in the basin of the small mountain river Ala-Archa, located on the northern slope of the Kyrgyz Range in Tien-Shan, which was chosen as an example due to its well-studied nature. Our approach could identify previously unknown factors of flow formation and assess the time and effectiveness of work in similar conditions. Full article

As global water scarcity becomes increasingly acute, water demand forecasting has emerged as a critical component in water resource management and planning. This review aims to comprehensively survey and analyze the current state of research, existing issues, and development trends in the field of water demand forecasting. Presently, there are numerous studies on water demand forecasting; however, most of the forecasting results tend to be overestimated. On the mechanistic level, research has gradually shifted from considering single factors to accounting for the complex influences of multiple factors. This paper summarizes the mechanism of water demand from the three levels of agriculture, industry, and residential life. In terms of forecasting methods, various techniques have been explored and applied, particularly new methods based on artificial intelligence and machine learning, which have demonstrated significant advantages in improving forecasting accuracy and handling nonlinear relationships. Despite the notable progress and practical achievements in water demand forecasting, several challenges and issues remain. Future research should focus on diversifying methodologies, comprehensively considering multiple influencing factors, further refining forecasting models and technical systems, strengthening uncertainty and risk management, and emphasizing practical applications and policy guidance. Full article

The Dinaric karst in the north differs from the rest of the karst in Croatia in terms of karstification depth. The infiltrating precipitation drains in cascades from deeply karstified mountainous areas to the shallow or fluviokarst, forming the tributaries of the Kupa River. Time series analyses were conducted on a 5-year dataset to elucidate the hydrogeological conceptual model of the area and clarify disparate findings from tracer tests under varying hydrological conditions. The flow duration curve, autocorrelation functions, and recession curves were used to evaluate the spring discharge variability, the karstification degree, and the karst aquifer’s size. The crosscorrelation function and temperature dynamics were employed to assess the spring’s response to recharge and the hydrogeological system behavior. Comparative analysis with previous studies was conducted to contextualize the obtained results. The research outcomes delineated several key findings: (i) the deep karst zone is less developed than the shallow karst zone; (ii) groundwater exchange is significantly faster in shallow karst; (iii) groundwater divides in the Kapela Mountain are zonal; (iv) the homogenization of groundwater occurs during periods of high water levels; (v) fast water exchange transpires without concurrent groundwater temperature homogenization; and (vi) a definition of the boundary between deep and fluviokarst in Croatia. Full article

This study investigated the energy requirement for running desalination units coupled to cogeneration plants. Various cogeneration systems were explored using power- and heat-allocated approaches. The specific work and heat necessary for operating different desalination systems were determined. The investigation revealed that the specific work and heat remain consistent regardless of the desalination daily capacity. It was observed that the energy demand for operating a desalination system mainly relies on power plant efficiency. The investigation revealed that the energy demand for a plain multi-effect desalination system was lower than that for multi-effect desalination with thermal vapor compression. Additionally, the energy requirement for a multi-effect desalination system with preheaters was lower than that for plain multi-effect desalination. Comparisons also indicated that the energy demand of multi-stage flash exceeds that of different multi-effect desalination systems. Based on the primary thermal energy input, a universal performance ratio was used to evaluate the desalination unit performance. Furthermore, a new correlation was proposed to predict the universal performance ratio. Full article

Rainfall-runoff nitrogen (N) pollution has emerged as the primary source of water contamination due to rapid urbanization. Green infrastructure (GI), as the representative measure, is widely used in controlling N pollution in runoff. However, there is limited research on the impact of woody plants on N reduction in GIs. Therefore, this study aimed to investigate the influence and relationship of Sophora japonica (with tap root) and Malus baccata (with fibrous root) on N removal in GIs. Utilizing the advanced root analysis software WinRHIZO (version 4.0b), a meticulous examination of the morphological traits of plant roots was conducted. The findings unveiled a striking contrast between the root systems of two species: S. japonica primarily boasts a vertically oriented root configuration, whereas M. baccata’s root system is characterized by an extensively lateral, or horizontal, growth pattern. Specifically, in comparison to S. japonica, the horizontal roots of M. baccata demonstrated a substantial superiority, with their total root length measuring 10.95 times longer, the surface area spanning 6.25 times wider, and the cumulative volume being 3.93 times greater. For comparing the load reduction rates on runoff NH₃-N, NO₃-N, and TN of the different root morphologies’ GIs, S. japonica GI had the highest purification effect on the three pollutants, and the average load reduction rates of three pollutants reached 67.74%, 33.83%, and 38.96%, respectively, which were 11.42%, 27.46%, and 6.16% higher than those of the control. The variance contribution rate of vertical root and horizontal root characteristics on runoff nitrogen load reduction accounted for 86.47% of the total root contribution rate. The volume of vertical roots emerged as the most crucial characteristic factor affecting the reduction of N load. Full article

In 2023, this study monitored nine types of antibiotics in the influent and effluent of wastewater treatment plants (WWTPs) in the urban and suburban areas of Tangshan. The total antibiotics concentration detected in influent WWTPs was highest in winter, followed by spring, summer, and autumn. The antibiotics concentration in influent and effluent urban WWTPs was higher than that in the suburban WWTPs in spring, summer, and winter, while the trend was reversed in autumn. Roxithromycin and oxytetracycline had a risk quotient (RQ) value of ≥0.1 in the effluent of WWTPs in winter, indicating that they are medium-risk antibiotics that pose a risk to the aquatic ecosystem after discharge. In the study area, the per capita pollution load of antibiotics was highest in spring, summer, and autumn for sulfamethoxazole, while it was highest in winter for ofloxacin. In the urban area, the use of roxithromycin, sulfamethoxazole, sulfamethoxazole, and ofloxacin was highest in spring, summer, autumn, and winter, respectively, while in suburban areas, the use of sulfamethoxazole, norfloxacin, sulfamethoxazole, and ofloxacin was highest during the same period. The use of antibiotics in the urban area was one order of magnitude higher than that in suburban areas, indicating a possible overuse of antibiotics in urban environments. Full article

Eutrophication in water reservoirs releases algal organic matter (AOM), a key precursor to the formation of disinfection by-products (DBPs) during the disinfection process. Typical drinking water treatment is not efficient for AOM removal, and advanced treatments are necessary for the removal of residual AOM before chlorination. UV-based technology with PS and TiO₂ is widely used as a pre-oxidation step in water treatment; however, no publications have focused on them for AOM degradation. In this context, this work investigated the effect of oxidant concentration (0.1 to 0.5 g∙L⁻¹) and pH (6 to 10) on AOM degradation with TiO₂/UV and persulfate (PS)/UV using response surface methodology. In general, PS/UV was more effective in removing protein, while TiO₂/UV was more effective in carbohydrate degradation. TiO₂/UV removals varied from 27 to 57% for protein and from 48 to 86% for carbohydrates. The optimal condition (57% for protein and 86% for carbohydrates) was obtained using 0.5 g∙L⁻¹ TiO₂ at pH 10. PS/UV removals varied from 33 to 81% for protein and from 24 to 53% for carbohydrates. The optimal condition (81% for protein and 53% for carbohydrates) was obtained using 0.5 g∙L⁻¹ PS concentration at pH 8. Degradation kinetics showed a good fit to the pseudo-first-order model (R² > 95%) for both processes. The DBP formation reductions observed with TiO₂/UV—trihalomethane (THM) (85 to 86%) and chloral hydrate (CH) (94 to 96%)—were similar to the efficiencies observed for PS/UV—THM (87 to 89%) and CH (83 to 88%). These results show the efficiency of UV-based technology for AOM degradation and the control of DBP formation. Full article

A novel heterotrophic aerobic denitrifying Pseudomonas hunanensis strain DC-2 was screened from the sediments of Lake Dianchi and identified with high nitrification/denitrification ability. Within 30 h, the removal efficiency of ammonium-N and nitrate-N could reach 98.8% and 88.4%, respectively. The results of the single-factor experiments indicated that strain DC-2 exhibited excellent denitrification ability under the conditions of using sodium citrate as the nitrogen source, with an initial pH of 7, a C/N ratio of 10, and a temperature of 30 °C. Nitrogen balance experiments suggested that this strain removed N mainly via assimilation. Moreover, the N removal pathway was explored by genome and enzymatic assays, and a complex nitrogen metabolism pathway was established, including heterotrophic nitrification-aerobic denitrification (HN-AD), assimilatory reduction of nitrate (ANRA), and ammonia assimilation. Additionally, strain DC-2 was immobilized into particles for denitrification, demonstrating excellent efficacy in continuous total nitrogen removal (84.8% for TN). Hence, strain DC-2 demonstrated significant potential in treating real aquaculture wastewater. Full article

Most cyanobacteria that form harmful algal blooms (HABs) in inland waterbodies can overwinter in sediments. This field demonstration within an urban pond was conducted to bolster a database on the novel use of algaecide treatments to proactively target overwintering cyanobacteria located in sediments prior to HAB formation. In March 2023, a peroxide-based algaecide was applied to sediments of a water feature located in urban Kansas City, Kansas, and cyanobacteria responses were measured over subsequent weeks and months. Multiple lines of evidence were used to discern the impacts of proactive treatments on overwintering cells in sediments and HAB severity throughout the growing season. Although results of the measured cyanobacterial responses were mixed, three of five lines of evidence indicated proactive algaecide treatments were effective at decreasing the transfer of cyanobacteria to the water column and HAB severity during months when HABs tended to occur. Microcystin concentrations immediately post-treatment (hours) remained at the analytical detection limit (0.10 µg/L) and were below USEPA risk-based thresholds, highlighting the benefits of application prior to the exponential growth phase of toxin-producing cyanobacteria. These results expand the dataset and methodology for field-scale proactive algaecide applications targeting overwintering cyanobacterial cells in sediment to mitigate and delay HAB development. Full article

Whether the phosphorus removal chemical in wastewater treatment plants (WWTPs) can be accurately dosed not only affects the compliance of the effluent total phosphorus but also has a huge impact on sludge production and energy consumption during the wastewater treatment process. For the effluent from the secondary sedimentation tank of a wastewater treatment plant in southern China, based on experimental screening of the optimal pH value, chemical types and concentrations of chemicals, coagulation time, etc., a dynamic dosage prediction feedforward model for chemical phosphorus removal agents in the effluent from the secondary sedimentation tank of the WWTPs was developed to predict the most economical dosage of the chemicals. Meanwhile, combined with the adaptive fuzzy neural network P feedback control algorithm, dynamic real-time control of chemical dosing was achieved. Through micro-control design, a software model for signal collection and feedback in a specific phosphorus removal scenario was formed, and an automatic control system for chemical dosing was ultimately developed for a WWTP in a city in southern China. After stable operation for two months, the system achieved a 100% compliance rate for effluent total phosphorus (TP) concentration and a 67% improvement in effluent stability, helping the wastewater treatment plant achieve stable and precise control of the phosphorus removal process in the secondary sedimentation tank effluent, which is conducive to further promoting its implementation of low-carbon pathways. Full article

The present study examines the recent evolution of a cliff coast along the Aegean Sea, considering its geotectonic context, oceanographic factors, sediment dynamics, and human impact. Initially, the formation of this coastal stretch was influenced by neotectonic faults, oriented both semi-parallel and diagonally relative to the present coastline orientation (NE–SW). Subsequently, the delivery of terrestrial sediment from ephemeral rivers and cliff erosion, along with nearshore wave-induced hydrodynamics have played a secondary role in shaping its current configuration, which includes a beach zone along the base of the cliff. This secondary phase of coastal evolution occurred over the past 4–5 thousand years, coinciding with a period of slow sea level rise (approximately 1 mm/year). Evidence such as uplifted notches and beachrock formations extending to around 5 m water depth suggests intervals of relative sea level stability, interrupted by episodic tectonic events. Anthropogenic interventions, related to both changes in coastal sediment budget and coastal engineering projects, have caused beach erosion, particularly in its central and northern sectors. Full article

Core wall rockfill dams are susceptible to cracking at the dam’s crest, as well as collapse and settlement of the rockfill during storage and operation periods, particularly due to rapid fluctuations in the water level in pumped storage power stations. Most studies on the impact of fluctuations in the reservoir’s water level on dam deformation have considered fluctuations of less than 5 m/d, while pumped storage power stations experience much larger fluctuations. Additionally, the seepage and stress fields within the dam’s rock and soil interact and influence each other. Few studies have used the coupling theory of seepage and stress to analyze seepage and deformation in core wall rockfill dams. To address these issues, a finite element model using seepage–stress coupling theory was utilized to investigate the variations in the phreatic line, earth pressure, and deformation of a core wall rockfill dam due to rapid fluctuations in the reservoir’s water level. Additionally, the results of the finite element simulation were compared with and analyzed alongside safety monitoring data. The results indicated that, upon a sudden decrease in the reservoir’s water level, there was a lag in the decline of the phreatic line in Rockfill I, which created a large hydraulic gradient, resulting in a reverse seepage field on the dam’s slope surface and generating a drag force directed upstream. Consequently, a significant concentration of stress occurred on one-third of the upstream slope surface of the dam and the seepage curtain, and the increase in horizontal displacement was substantially greater than the increase in settlement from one-third of the rockfill’s height to the dam’s foundation. The deformation was more sensitive to the lowest water level of the reservoir rather than to the fastest rate of decline. Sudden rises in the reservoir’s water level result in decreased horizontal displacements and settlement of the dam. Amid rapid fluctuations of the reservoir’s water level, changes in the vertical earth pressure were more pronounced at the bottom of the core wall than in its midsection. Compared with the core wall, variations in the vertical earth pressure in the upstream and downstream filter layers were minor at similar elevations. A peak horizontal displacement of 6.5 mm was noted at one-third the height of Rockfill I, with the greatest increase in settlement of 3.5 mm at the dam’s crest. To ensure a project’s safety, it is crucial to control the elevation of the lowest point during a sudden drop in the reservoir’s level and to carefully monitor for cracks or voids within approximately one-third of the dam’s height in Rockfill I and at the dam crest. This study’s results provide a scientific basis for assessing core wall rockfill dams’ health and securing long-term safety at pumped storage power facilities. Full article

In chemical production processes in China, a huge volume of salt waste is produced, contributing to environmental pollution due to the lack of proper treatment procedures to manage this waste effectively. With the current lack of proper treatment methods for salt waste disposal, landfill emerges as the predominant disposal approach adopted in China, exacerbating environmental concerns associated with the accumulation of such waste. In addition, this method fails to reuse and recycle salt waste. This review paper presents pertinent research on the safe disposal and utilization of salt waste in China. Well-known valorization methods, such as oxidation, thermal treatment, washing separation, precipitation, and evaporation crystallization, are comprehensively reviewed. The current technologies for recovering resources from salt waste and recommendations for its treatment and valorization are analyzed. This research work offers a reference for future resource utilization of industrial salt waste. Full article

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

Groundwater contamination source (GCS) parameter identification can help with controlling groundwater contamination. It is proverbial that groundwater contamination concentration observation errors have a significant impact on identification results, but few studies have adequately quantified the specific impact of the errors in contamination concentration observations on identification results. For this reason, this study developed a Bayesian-based integrated approach, which integrated Markov chain Monte Carlo (MCMC), relative entropy (RE), Multi-Layer Perceptron (MLP), and the surrogate model, to identify the unknown GCS parameters while quantifying the specific impact of the observation errors on identification results. Firstly, different contamination concentration observation error situations were set for subsequent research. Then, the Bayesian inversion approach based on MCMC was used for GCS parameter identification for different error situations. Finally, RE was applied to quantify the differences in the identification results of each GCS parameter under different error situations. Meanwhile, MLP was utilized to build a surrogate model to replace the original groundwater numerical simulation model in the GCS parameter identification processes of these error situations, which was to reduce the computational time and load. The developed approach was applied to two hypothetical numerical case studies involving homogeneous and heterogeneous cases. The results showed that RE could effectively quantify the differences caused by contamination concentration observation errors, and the changing trends of the RE values for GCS parameters were directly related to their sensitivity. The established MLP surrogate model could significantly reduce the computational load and time for GCS parameter identification. Overall, this study highlights that the developed approach represents a promising solution for GCS parameter identification considering observation errors. Full article

Taking the Jiefangzha irrigation area of the Inner Mongolia Autonomous Region as the research area, the response relationships between the backscattering coefficient and radar frequency, radar incidence angle, root-mean-square height, correlation length, and soil water content under different conditions were simulated using advanced integral equations. The backscattering characteristics of exposed surfaces in cold and dry irrigation areas were discussed, and the reasons for the different effects were analyzed. Based on this, surface roughness models and statistical regression moisture inversion models were constructed through co-polarized backscatter coefficients and combined surface roughness. The correlation between the inverted surface roughness values and the measured values was R² = 0.7569. The correlation between the soil moisture simulation values and the measured values was R² = 0.8501, with an RMSE of 0.04. The findings showed a strong correlation between the values from the regression simulation and the measured data, indicating that the model can be applied to soil moisture inversion and has a good inversion accuracy. Compared with previous studies in the same area, the inversion model proposed in this paper has a higher accuracy and is more suitable for the inversion of soil moisture in the Jiefangzha irrigation area. These findings can support research on the water cycle and water environment assessment in the region. Full article

Beira Lake, located in Colombo, Sri Lanka, has suffered severe anthropogenic impacts, with previous restoration attempts failing due to a limited understanding of pollutant dynamics. Aiming to fill this gap, a comprehensive study was conducted during dry and wet seasons to assess the spatiotemporal water pollution of Beira Lake, employing key physicochemical parameters, numerical indices, and remote sensing analysis. The water pollution index (WPI) results categorize Beira Lake as highly polluted, with WPI values ranging from 2.38 ± 0.92 in the wet season to 2.53 ± 1.32 in the dry season. Comparatively higher COD levels recorded in the Beira Lake network, especially for Gangarama Lake show significant pollution levels during both the dry and wet seasons, e.g., the highest COD levels, at 306.40 mg/L, were observed during the wet season. The Trophic State Index (TSI) results indicate eutrophic and hypereutrophic conditions in Beira Lake, which are particularly pronounced during the wet season. The heavy metal pollution index (HPI) results suggest elevated heavy metal concentrations in Beira Lake, especially in the wet season. Combined with field investigation results, a remote sensing data analysis between 2016 and 2023 reveals significant improvements in water transparency, suggesting positive effects of recent management interventions. Parameters demanding attention include COD, nitrate, and total phosphate levels due to their consistent exceedance of permissible limits. The PCA results of indices correlations between wet and dry seasons offer valuable insights into the complex dynamics of Beira Lake’s water quality. The study makes recommendations for restoring Beira Lake, including stringent pollution controls, regular dredging, green infrastructure implementation, implementing new rules and regulations, and community engagement. Full article

The integrated assessment of ecological quality in estuarine ecosystems holds significant importance for environmental management. Previous monitoring programs predominantly focused on environmental data, lacking a comprehensive quality assessment approach. To address this gap, this study aimed to integrate environmental factors with macrofaunal community information to evaluate the ecological quality status of the Yellow River Estuary. A total of 13 stations were routinely monitored in August for four consecutive years to collect environmental and biological data. Candidate indicators were screened based on variation coefficients, distribution ranges, and redundancy analysis, identifying 16 indicators belonging to three categories (i.e., seawater, sediment, and biology). The model fit and the interrelationship of the components were determined using structural equation modelling (SEM). The main results were as follows. (1) A total of 144 macrofaunal taxa, belonging to eight animal phyla and 98 families, were identified, with a dominance of Annelida (37.8%) and Mollusca (33.3%). The environmental variables most strongly correlated with the macrofaunal community were TOC, DO, Cd, and Md. (2) NO₂ and heavy metals represented the two most direct factors of environmental pollution, while the factor load of biodiversity indices (H’, J, and D) was large in the biology category. (3) The evaluation results indicated that 78.85% of the total samples were between the average and upper levels of ecological quality, but only 7.69% of samples were at the “high” level. The framework system for the evaluation of ecological quality constructed in this study provides a theoretical and practical basis for the evaluation of the effectiveness of conservation management of the Yellow River Estuary. Full article

Urban flooding is one of the main challenges affecting sustainable urban development worldwide, threatening the safety and well-being of communities and citizens. The aim of this study is to assess the development and trends in urban flood resilience at the city scale, as well as to improve the resilience of cities to these risks over time. The study constructs a model for assessing urban flood resilience that incorporates economic, social, ecological, and managerial aspects and assesses them through a range of indicators identified in the literature. The comprehensive evaluation model of Network Analysis Method–Entropy Weight Method–The Distance between Excellent and Inferior Solutions (ANP-EWM-TOPSIS) was used to empirically investigate the flood resilience characteristics of Nanjing from 2010 to 2021. There are two main findings of the study: firstly, the flood resilience of Nanjing gradually improves over time, as the economic flood resilience steadily increases, while the social, ecological, and management flood resilience decreases; and secondly, during the study period, barriers caused by economic and regulatory factors in Nanjing decreased by 33.75% and 23.72%, respectively, while barriers caused by social and ecological factors increased by 32.69% and 24.68%, respectively. The novelty of this study is the introduction of a “barrier degree” model, which identifies and highlights barriers and obstacles to improving urban flood resilience and provides new insights into improving urban flood resilience at the city scale. Full article

As green infrastructure has evolved, grass swales have become integral components of stormwater management. Manning’s equation is commonly used to describe the hydraulic characteristics of grass swales. However, due to flow loss from infiltration, grass swales often deviate from the assumptions of Manning’s equation, potentially leading to significant errors in grass swale flow rate calculations. In this study, we systematically investigated changes in flow rates in grass swales under various constant inflow rate conditions. The results indicated that the suitability of using Manning’s equation to estimate flow rate in grass swales varies with inflow rate. At an inflow rate of 3.00 m³/h, the discrepancy between the measured and the estimated flow rates by Manning’s equation was the smallest, ranging from −0.24 to 0.19 m³/h. At lower inflow rates (1.00 to 2.00 m³/h), Manning’s equation underestimated the flow rates by 0.16 to 0.47 m³/h; at higher rates (4.00 m³/h), it overestimated the flow rates by 0.01 to 0.61 m³/h. Considering infiltration losses as the primary cause of these errors, we proposed an improved Darcy’s formula for estimating the infiltration rates in grass swales, along with a modified Manning’s equation for more accurate flow rate calculations. The modified Manning’s equation provides enhanced accuracy in calculating flow rates in grass swales compared to the traditional version. Full article

Argentina stands as the leading producer and exporter of olive products in the Americas, with the province of La Rioja as its main productive area. Since the 1990s, the olive grove cultivated area and related agro-industry in La Rioja have expanded. However, the resulting wastewater has generally been neglected. The water footprint (WF) provides information about the water volume consumed and polluted by a production process. Since the 1990s, agricultural and agro-industrial activities in La Rioja have experienced substantial growth. This study aims to analyze the generation, quality, and management of Oil Mill Wastewater (OMWW) using the grey WF of chloride and nitrate as an indicator and focusing on two olive mills (OM) in La Rioja. Additionally, it seeks to examine the relationship between the international trade of provincial olive oil and the estimated grey WF. For the diagnosis of OMWW generation, a description of the production process was made coupled with flow and physico-chemical characterization. The total grey WF was 8.69 and 45.5 L water/L olive oil for OM 1 and OM 2, respectively. Nitrate was identified as the critical pollutant. The grey virtual water export related to the export of olive oil was 5569 m³ for OM 1 and 28,000 m³ for OM 2. The provincial grey virtual water export related to olive oil was 161,955 m³ with major trade destinations including Spain, the United States, and Brazil. The article analyses for the first time the grey WF of olive oil industries and assess the related grey virtual water exports. This research represents a step forward in the knowledge of wastewater management in the olive oil sector and facilitates the search for solutions to minimize negative environmental impacts while promoting cleaner production. Full article

As the medium of geological information, groundwater provides an indirect method to solve the secondary disasters of mining activities. Identifying the groundwater regime of overburden aquifers induced by the mining disturbance is significant in mining safety and geological environment protection. This study proposes the novel data-driven algorithm based on the combination of machine learning methods and hydrochemical analyses to predict anomalous changes in groundwater levels within the mine and its neighboring areas induced after mining activities accurately. The hydrochemistry analysis reveals that the dissolution of carbonate and evaporite and the cation exchange function are the main hydrochemical process for controlling the groundwater environment. The anomalous change in the hydrochemistry characteristic in different aquifers reveals that the hydraulic connection between different aquifers is enhanced by mining activities. The continuous wavelet coherence is used to reveal the nonlinear relationship between the groundwater level change and external influencing factors. Based on the above analysis, the groundwater level, precipitation, mine water inflow, and unit goal area could be considered as the input variables of the hydrological model. Two different data-driven algorithms, the Decision Tree and the Long Short-Term Memory (LSTM) neural network, are introduced to construct the hydrological prediction model. Four error metrics (MAPE, RMSE, NSE and R²) are applied for evaluating the performance of hydrological model. For the NSE value, the predictive accuracy of the hydrological model constructed using LSTM is 8% higher than that of Decision Tree algorithm. Accurately predicting the anomalous change in groundwater level caused by the mining activities could ensure the safety of coal mining and prevent the secondary disaster of mining activities. Full article

In this paper, a unitary method for the solution of transient cavitating flow in viscoelastic pipes is proposed in the framework of the method of characteristics (MOC) and a Z-mirror numerical scheme (MOC-Z model). Assuming a standard form of the continuity equation allows the unified treatment of both viscoelasticity and cavitation. An extension of the MOC-Z is used for Courant numbers less than 1 to overcome a few cases with numerical instabilities. Four viscoelastic models were considered: a Kelvin–Voigt (KV) model without the instantaneous strain, and three generalised Kelvin–Voigt models with one, two, and three KV elements (GKV1, GKV2, and GKV3, respectively). The use of viscoelastic parameters of KV and GKV models calibrated for transient flow tests without cavitation allows good comparisons between experimental and numerical pressure versus time for transient tests with cavitation. Whereas for tests without cavitation, the mean absolute error (MAE) always decreases when the complexity of the model increases (from KV to GKV1, GKV2, and GKV3) for all the considered tests, this does not happen for tests with cavitation, probably because the decreasing capacity of parameter generalization for the increasing complexity of the model. In particular, in the examined cases, the KV model performs better than the GKV1 and the GKV3 models in three cases out of five, and the GKV2 model performs better than the GKV3 model in three cases out of five. Furthermore, the GKV2 model performs better than the KV model only in three cases out of five. Full article

Anaerobic digestion (AD) is a promising method for resource recovery from various wastes. Compared to the conventional single-stage AD process, a two-stage AD process with separate H₂ and CH₄ production provides higher energy recovery efficiency and enhanced operation stability. The stage separation makes it possible to apply optimal conditions for different functional microorganisms in their respective stages. This review elaborates the mechanisms of the two-stage AD process and evaluates recent research trends on this topic. A comprehensive comparison between single- and two-stage AD processes is made from the perspective of biogas production, organics degradation, energy recovery, and operation stability. The main influence factors on the two-stage AD process are discussed, including substrates, inoculum, and operation parameters, such as pH, temperature, etc. Upgrading technologies for the two-stage AD process are assessed. The microbial communities in the two-stage AD process for treating different substrates and the influence factors on microbial systems are also summarized. Furthermore, future research opportunities for enhancing the application of this technology are highlighted. Full article

This review article addresses the increasing environmental concerns posed by synthetic dyes in water, exploring innovative approaches for their removal with a focus on zero-valent iron nanoparticles (nZVIs) synthesized through environmentally friendly methods. The article begins by highlighting the persistent nature of synthetic dyes and the limitations of conventional degradation processes. The role of nanoparticles in environmental applications is then discussed, covering diverse methods for metallic nanoparticle production aligned with green chemistry principles. Various methods, including the incorporation of secondary metals, surface coating, emulsification, fixed support, encapsulation, and electrostatic stabilization, are detailed in relation to the stabilization of nZVIs. A novel aspect is introduced in the use of plant extract or biomimetic approaches for chemical reduction during nZVI synthesis. The review investigates the specific challenges posed by dye pollution in wastewater from industrial sources, particularly in the context of garment coloring. Current approaches for dye removal in aqueous environments are discussed, with an emphasis on the effectiveness of green-synthesized nZVIs. The article concludes by offering insights into future perspectives and challenges in the field. The intricate landscape of environmentally friendly nZVI synthesis has been presented, showcasing its potential as a sustainable solution for addressing dye pollution in water. Full article

The rural population in the Dry Zone of Sri Lanka is largely affected by Chronic Kidney Disease of Unknown etiology (CKDu). According to the multidisciplinary research carried out so far, quality of groundwater is considered one of the possible causative factors for CKDu. Therefore, assessment of the quality of groundwater being used for drinking and its evolution mechanism is the key to identifying the linkage between CKDu and drinking water. This study aimed to perform a detailed investigation on groundwater sources using isotopic, chemical, and hydrogeological methods in the CKDu-endemic (site A) and the control area (sedimentary formation—site B) in the Malwathu Oya basin and the control areas in the Malala Oya basin (site C) selected for a systematic comparison. Our investigation shows that elevated levels of TDS, magnesium, and fluoride in the shallow groundwater affected by climatic, geochemical, and hydrogeological processes may contribute to the CKDu in the Dry Zone of Sri Lanka. All the groundwater samples analysed have exceeded the hardness threshold. Prominent Mg hardness proportion together with excess F⁻ in the CKDu endemic area may produce nephrotoxic MgF₂ complexes that may trigger renal damage. In contrast, NaF complexes in the CKDu control area leads to reduction of F⁻ toxicity in the human body. Elevated F⁻ and Mg²⁺ are found in site A, low F⁻ and high Mg²⁺ in site B, and either combinations of low F⁻ and low Mg²⁺, high F⁻ and low Mg²⁺, or low F⁻ with high Mg²⁺ in site C. TDS, hardness, Mg²⁺, Na⁺, and F⁻ are formed with different mechanisms in the three selected areas. The primary process that regulates the evolution of groundwater types and contents in sites A and C is the weathering of silicates. Similarly, in site A, carbonate dissolution and reverse ion exchange are quite strong. Cation exchange and evaporite dissolution are more pronounced in site C. Shallow groundwaters are evapo-concentrated, hence their quality deteriorates more significantly than the deep groundwater in the CKDu endemic area. Dilution decreases the ion content in site A while evaporite dissolution increases it in site C after the rainy season. Evaporation and seawater mixing affect the quality of groundwater in site B. It is also found that a statistically significant difference exists in the F⁻/Na⁺, F⁻/Mg²⁺, and F⁻/Ca²⁺ between the endemic and control areas. Intensive rock weathering combined with desorption has added excess F⁻ to the groundwater in site A, while cation exchange and fluorite dissolution are contributing factors in site C. Full article