Water

Water quality sampling and monitoring are fundamental to water environmental protection. The purpose of this study was to develop a water quality sampling and multi-parameter monitoring system mounted on a multi-rotor unmanned aerial vehicle (UAV). The system consisted of the UAV, water sampling and multi-parameter detection device, and path planning algorithm. The water sampling device was composed of a rotating drum, a direct current (DC) reduction motor, water suction hose, high-pressure isolation pump, sampling bottles, and microcontroller. The multi-parameter detection device consisted of sensors for potential of hydrogen (pH), turbidity, total dissolved solids (TDS), and a microcontroller. The flight path of the UAV was optimized using the proposed layered hybrid improved particle swarm optimization (LHIPSO) and rapidly-exploring random trees (RRT) obstacle avoidance path planning algorithm, in order to improve the sampling efficiency. Simulation experiments were conducted that compared the LHIPSO algorithm with the particle swarm optimization (PSO) algorithm and the dynamic adjustment (DAPSO) algorithm. The simulation results showed that the LHIPSO algorithm had improved global optimization capability and stability compared to the other algorithms, validating the effectiveness of the proposed algorithm. Field experiments were conducted at an aquaculture fish farm, and the device achieved real-time monitoring of three water quality parameters (pH, TDS, turbidity) at depths of 1 m and 2 m. A rapid analysis of three parameters (ammonia nitrogen, nitrite, dissolved oxygen) was performed in the laboratory on the collected water samples, and validated the feasibility of this study. Full article

The aim of this paper is to assess the extent to which the Sad-Kalan watershed in Iran participates in floods and rank the Sad-Kalan sub-watersheds in terms of flooding potential by utilizing multi-criteria decision-making approaches. We employed the entropy of a drainage network, stream power index (SPI), slope, topographic control index (TCI), and compactness coefficient (Cc) in this investigation. After forming a decision matrix with 25 possibilities (sub-watersheds) and 5 evaluation indices, we used four MCDM approaches, including the analytic hierarchy process (AHP), best–worst method (BWM), interval rough numbers AHP (IRNAHP), picture fuzzy with AHP (PF-AHP), and picture fuzzy with linear assignment model (PF-LAM, hereafter PICALAM) algorithms, to rank the sub-watersheds. The study results demonstrated that PICALAM exhibited superior performance compared to the other methods due to its consideration of both local and global weights for each criterion. Additionally, among the methods used (AHP, BWM, and IRNAHP) that showed similar performances in ranking the sub-watersheds, the BWM method proved to be more time-efficient in the ranking process. Full article

This work examines the adsorption in single- and multi-solute adsorption experiments of antibiotic and non-steroidal anti-inflammatory drugs, i.e., ciprofloxacin (CPX), sulfamethoxazole (SMX), ibuprofen (IBU), and diclofenac (DCF), onto sugarcane bagasse. The maximum experimental adsorption capacities of single components CPX, DCF, IBU, and SMX, were 0.98, 0.77, 0.61, and 0.51 mg/g, respectively, with decreases between 5 and 28% in multi-solute mixtures, assuming competitive adsorption. The experimental data of a single drug fitted a pseudo-second-order model, while the experimental isotherms fit the Freundlich model. The presence of CPX did not interfere with the adsorption of other solutes. The adsorption of SMX was lower in the presence of adsorption competitors than SMX single solution. The adsorption of binary systems adequately fitted the Sheindorf–Rebhun–Sheintuch model. The results showed that the competition process depends on each adsorbate and that sugarcane bagasse can adsorb drugs in multi-component systems. Full article

One quarter of the world’s population uses karst groundwater. Due to the complex hydrological conditions in karst areas, they are vulnerable to pollution. The study of the hydrochemical characteristics and environmental quality evaluations of karst groundwater is of great significance for the rational development and utilization of karst groundwater. The study area is located in the Mengzi area of Yunnan Province, which is a typical karst area. The groundwater in the study area was analyzed and evaluated by a statistical analysis, hydrogeochemical analysis, ion ratio and Nemerow’s index method (P_N). The results show that the hydrochemical types are mainly the Ca–HCO₃ and Ca–Mg–HCO₃ types. The main hydrochemical compositions of groundwater were controlled by carbonate dissolution. The results of the water quality evaluation show that the main pollutants in the study area are Mn, COD and NO₃⁻. Compared with groundwater, the concentration and exceeding rate of pollutants in surface water are much higher than those in groundwater. There is the possibility of groundwater pollution by surface water infiltration. The results reveal the characteristics of groundwater pollution in typical karst areas and provide a theoretical basis for the rational development and utilization of groundwater. Full article

Wind and wave conditions are limiting factors for economic activity, and it is very important to study the long-term variability of storm activity. The main motivation of this research is to assess the impact of wind variability on the storm activity in the Caspian Sea over the past 42 years. The paper presents the analysis of a number of storms based on the results of wave model WAVEWATCH III and the Peak Over Threshold method. The mean, maximum, and 95th percentile significant wave heights were analyzed by season. The highest waves were in the Middle Caspian Sea in winter. Detailed interannual and seasonal analyses of the number and duration of storm waves were performed for the whole Caspian Sea and its separate regions. Positive significant trends were found in the whole sea. Significant positive trends in the number and duration of storms were found for the North and Middle Caspian. In the South Caspian, the trends were negative and not significant. High correlations were found between the number of storms and events with wind speed > 10–14 m/s and 95th percentile wind speed. Positive trends in the number of storms in the Middle Caspian were caused by positive trends in extreme wind situations. Full article

A piano key weir (PKW), a new type of weir aiming to increase the discharge capacity of an existing dam, was recently designed. Despite a large body of research in this field, only a few studies were conducted on A-type triangular piano key weirs (TPKW) in straight channels. In this context, this present research sought to study the flow regime, stage–discharge relationship, and discharge coefficient. Experiments were carried out using nine TPKW models and three linear weirs (LW) as the control weirs. The results indicated that the triangular piano key weirs are capable of passing a higher discharge in similar laboratory conditions compared to linear key weirs due to their longer length. For a given h/P ratio (h is the water head over the weir crest, and P is the weir height) and constant length (L_e), an increase in the weir height from 0.07 m to 0.15 m decreases the discharge coefficient by approximately 20%. From sensitivity analysis, the most influential parameters for the tested TPKW models are the h/Le dimensionless ratio, followed by the P/L_e and Fr. Moreover, the discharge coefficient has a reverse trend when the dimensionless parameters h/P, h/L_e, and Froude number are increased. However, with decreasing h/L_e, the discharge coefficient of TPKW tends to that of a broad-crested weir because of local submergence. It is expected that the results obtained will be a reference for researchers who work in this field. Full article

Marine fish populations have suffered the consequences of overfishing for a long time, leading to a loss in biodiversity. Traditional methods have been historically used to survey fish diversity but are limited to commercial species, particularly on the high seas. Environmental DNA (eDNA) has been successfully used to monitor biodiversity in aquatic environments. In this study, we monitored fish diversity in the Clarion–Clipperton Zone (CCZ) of the Eastern Pacific Ocean using eDNA metabarcoding. Our results identified 2 classes, 35 orders, 64 families, and 87 genera. The genera Mugil, Scomberomorus, and Scomber had high relative abundance in the mesopelagic and demersal zone. Fish diversity varied with sampling sites, and the greatest number of species was found at a depth of 2500 m. Environmental changes drove fish aggregation, and our results indicated that Chla was negatively correlated with fish communities, while DO was positively correlated with fish communities. This study released the fish diversity pattern and the effects of the environment in the CCZ, which would provide useful information for biodiversity management and an environmental baseline for the International Seabed Authority. Full article

Unpredictable natural disasters brought by extreme climate change compound difficulties and cause a variety of systemic risks. It is thus critical to provide possibilistic scheduling schemes that simultaneously involve emergency evacuation and relief allocation. But the existing literature seldom takes emergency evacuation and relief supplies as a joint consideration, nor do they explore the impact of an unpredictable flood disaster on the scheduling scheme. A multi-stage stochastic programming model with updating information is constructed in this study, which considers the uncertainty of supply and demand, road network, and multiple types of emergency reliefs and vehicles. In addition, a fuzzy algorithm based on the objective weighting of two-dimensional Euclidean distance is introduced, through moderating an effect analysis of the fuzzy number. Computational results show that humanitarian equity for allocating medical supplies in the fourth period under the medium and heavy flood is about 100%, which has the same as the value of daily and medical supplies within the first and third period in the heavy scenarios. Based on verifying the applicability and rationality of the model and method, the result also presents that the severity of the flood and the fairness of resources is not a simple cause-and-effect relationship, and the consideration of survivor is not the only factor for humanitarian rescue with multi-period. Specifically, paying more attention to a trade-off analysis between the survival probability, the timeliness, and the fairness of humanitarian service is essential. The work provides a reasonable scheme for updating information and responding to sudden natural disasters flexibly and efficiently. Full article

Flood risk has increased distressingly, and the incidence of waterborne diseases, such as diarrhoeal diseases from bacteria, has been reported to be high in flood-prone areas. This study aimed to evaluate the flood risk patterns and the plausible application of flow cytometry (FCM) as a method of assessment to understand the relationship between flooding and waterborne diseases in Malaysia. Thirty years of secondary hydrological data were analysed using chemometrics to determine the flood risk patterns. Water samples collected at Kuantan River were analysed using FCM for bacterial detection and live/dead discrimination. The water level variable had the strongest factor loading (0.98) and was selected for the Flood Risk Index (FRI) model, which revealed that 29.23% of the plotted data were high-risk, and 70.77% were moderate-risk. The viability pattern of live bacterial cells was more prominent during the monsoon season compared to the non-monsoon season. The live bacterial population concentration was significantly higher in the midstream (p < 0.05) during the monsoon season (p < 0.01). The flood risk patterns were successfully established based on the water level control limit. The viability of waterborne bacteria associated with the monsoon season was precisely determined using FCM. Effective flood risk management is mandatory to prevent outbreaks of waterborne diseases. Full article

In the last decades, the Rif area in Morocco has been frequently affected by soil erosion due to intense rainfall events. In order to help farmers improve their lives and avoid damages caused by this phenomenon, a management project (the MCA Project) aiming to grow fruit trees has been realized. The objective of this study was to evaluate, in three provinces of Morocco, the effect on the hydrological response of selected erosion control management techniques combined with olive tree plantations. The investigated variables were the final infiltration (If), the imbibition of rainwater (Pi), the runoff coefficient (Kr), and the soil detachment (D). In particular, for each investigated soil utilization, three replications of a rain simulation test (80 mm/h) and soil sampling were conducted. Results for surface conditions demonstrate that under vegetation in matorral and fallow, the surface is covered at more than 75% with a high content of organic matter (OM) at 4.5% and 2.6%, respectively. Despite the compaction observed in those land uses, the surface area opened exceeded 90% in the study area. Regarding the soils physical properties, they were rich in silt at more than 40%; the rate of porosity is high where bulk density is low. At the Taounate site, low porosity was at 62% in fallow and at 55% in plowing, with high densities of 1.01 g/cm² and 1.2 g/cm², respectively. Tests also demonstrate that vegetation has an important role in moisture conservation in the depths of 0 to 10 cm at all sites with macroagregate stability (MA%) compared to plowing sites. In terms of soil hydrology, vegetation reduces the runoff because, under matorral (it was at 0%), it avoids soil erosion. Full article

It is of great practical significance to accurately distinguish the different water supply sources of rivers and lakes under climate change for regional water resources utilization. This study examines the impact of climate change on the hydrological processes of the Ranwu Lake basin in the southeastern Tibet Plateau. The authors used China Meteorological Forcing Dataset (CMFD) historical data, CanESM5′s future climate predictor, and the SPHY model to analyze trends in temperature, precipitation, and water supply sources in the basin. The study found that warming in the basin was higher than that in the Tibet Plateau, with high-altitude areas and winter showing more significant warming. From 1998 to 2018, precipitation in the basin showed a trend of fluctuation and decline. The study also found that glacial meltwater accounted for the majority of total runoff in the basin (54.13%), while snow meltwater, rainfall, and baseflow accounted for about 22.98%, 11.84%, and 11.06%, respectively, on average in recent years. The total runoff in the Ranwu Lake Basin will continue to decrease due to the accelerating retreat of glaciers, with the hydrological process transforming from being dominated by glacier processes to rain–snow processes. The study also predicts that three-quarters of glaciers in the basin will vanish within the next forty years, and by 2100, only around 20% of glaciers will remain. Full article

As one of the important policy measures to promote water conservation and efficient utilization, the evaluation of water resources tax reform policy regarding its water saving and economic impact (WSEI) is a fundamental prerequisite for policy implementation. In this study, multiple types of water production modules, including surface water, groundwater, and unconventional water, were integrated into a CGE model. Hebei Province, the first pilot area in China, was used as a case study. Through a “with–without” comparative analysis scenario, three water resources tax policy simulations were designed to address the three key issues, and the results showed that the implementation of water resources tax policy would have a certain negative impact on industry economic output in the short term, but it could effectively suppress the use of conventional water and promote the utilization of unconventional water, which is beneficial for long-term water resource conservation and sustainability. The imposition of higher differential tax rates on high water-consuming industries is more effective in further promoting the use of unconventional water and reducing the use of conventional water to achieve water conservation targets. Moreover, providing tax refunds as subsidies to water-using industries could alleviate the economic impact of water resources tax and promote water conservation. From the perspectives of water quantity, water use efficiency, and economic impact, the optimal policy scenario (S3) was selected, involving implementing differential water resources tax rates of 23% for high water-consuming industries and 18% for general water-consuming industries, coupled with tax refunds and subsidies for sectors. Based on this, corresponding recommendations in terms of differential tax rate setting, tax utilization, government regulation, and agricultural water resources tax collection were provided. These findings can offer a scientific reference for the formulation and implementation of water resources tax policies in other regions. Full article

Disasters triggered by natural hazards are becoming more frequent and more intense, causing damage to infrastructure and causing loss of life. One way to reduce disaster risk is by evacuating the hazardous area. However, despite the amount of literature that exists on evacuation behavior, there is still a lack of agreement on which variables can be used as predictors for individuals (or households) to actually evacuate. This lack of agreement can be related to the many variables that can affect the evacuation decision, from demographics, geographic, the hazard itself, and also local or cultural differences that may influence evacuation. Hence, it is essential to analyze and understand these variables based on the specifics of a case study. This study aims to find the most significant variables to be used as predictors of evacuation on the island of Sint Maarten, using data collected after the disaster caused by Hurricane Irma in September 2017. The results suggest that the variables gender, homeownership, percentage of property damage, quality of information, number of storeys of the house, and the vulnerability index are the most significant variables influencing evacuation decisions on the island. We believe the results of this paper offer a clear view to risk managers on the island as to which variables are most important in order to increase evacuation rates on Sint Maarten and to plan more efficiently for future evacuations. In addition, the variables found in this study have the potential to be the base information to set up, validate, and calibrate evacuation models. Full article

Water can act as a vector for several microbes with significant pathogenic potential for both humans and animals. Waterborne infections are a critical public health concern as they cause more than 3.4 million deaths annually. Total and thermotolerant coliforms and intestinal enterococci have traditionally been used to assess the quality and suitability of drinking water. The aim of this study was to evaluate the microbiological quality of groundwater from six sub-basins located in the upper Choluteca River basin in Honduras and to determine the E. coli phylogroups isolated in these samples. Our findings show high rates of fecal contamination, which suggests that the groundwater in the basin is unsafe for human consumption. Phylogroups B1 and D were the most frequent among 99 E. coli isolates, while C and F were the least frequent phylogroups. Measures must be taken to raise awareness about sanitation and good practices for the management of household waste as well as the waste generated by agro-industrial activity and livestock. Full article

Non-indigenous species (NIS) represent one of the greatest threats to biodiversity and ecosystem functioning, altering invaded habitats, competing with native species, and eventually becoming pests. The Mediterranean Sea is a marine biodiversity hotspot, with its coasts being densely populated and its living resources fished since ancient times. As a result of such a long history of exploitation, the whole basin is exposed to a wide array of human pressures, with their combined effects on marine ecosystems being amplified by ongoing climate change. Caulerpa cylindracea Sonder, 1845, is a non-indigenous invasive seaweed widely distributed in the coastal habitats of the Mediterranean Sea, which ultimately affects marine biodiversity and ecosystem functioning. Here, a systematic literature analysis on the consumption of the NIS Caulerpa cylindracea by Mediterranean native and NIS species is provided, focusing on the benefits and drawbacks for the native biota and human health. The present review aims to synthetise knowledge and provide tools to manage the occurrence of the invasive seaweed C. cylindracea in the Mediterranean Sea, encouraging an ecosystem-based approach to the management of the ecological, economic, and social effects of the successful expansion of this NIS. Full article

Anaerobic digestion is a promising technology for treating and disposing of oily sludge, but the presence of oil in the sludge reduces methane production and sludge volume reduction. To overcome this limitation, this study creatively reports the use of magnetite to enhance methane production in oily sludge mesophilic anaerobic digestion and elucidates the underlying mechanism. Results show that the addition of magnetite increases methane production, with a 5% magnetite content leading to a 1.42-fold increase in cumulative methane output compared to the blank. Mechanistically, magnetite accelerates the release of organic matter, promotes oil degradation, increases volatile fatty acids (VFA) accumulation, and reduces the proportion of propionate. Additionally, magnetite alleviates pH decreases and increases the release of ammonia nitrogen and phosphate, resulting in effective sludge reduction, with volatile suspended solids (VSS) reduction ranging from 26.9% to 32.6%, higher than that of the blank. Moreover, magnetite accelerates electron transfer and increased the relative abundance of microorganisms associated with methane production, with the relative abundance of Methanosarcina increasing to 37.6~38.5% due to the presence of magnetite. This study provides a theoretical framework for effectively utilizing oily sludge through the application of magnetite. Full article

The current standards used for nitrogen pollution evaluation are lacking, and scientific classification methods are needed for nitrogen pollution to improve water quality management capabilities. This study addresses the important issue of assessing surface water nitrogen pollution by utilizing two advanced multivariate statistical techniques: self-organizing maps (SOMs) obtained using the K-means algorithm and the Hasse diagram technique (HDT). The research targets of this study are the rivers of the megacity Chengdu, China. Samples were collected on a monthly basis in 2017–2020 from different sites along the rivers, and their nitrogen pollution parameters were determined. The grouping of nitrogen pollution parameters and the clustering of sampling events using SOMs facilitate the preprocessing required for the HDT, wherein clusters are ordered according to the pre-clustered water sampling events. The results indicate that nitrogen pollution in the Chengdu River Basin, which is prominent and mainly driven by nitrate nitrogen, can be categorized into five levels. The nitrogen pollution in Tuo River is serious. Although the degree of ammonia nitrogen pollution in Jin River is higher, the pollution range is smaller. Furthermore, these results were evaluated by the SOMs and HDT to be clear and reliable. Overall, these findings can provide a basis for local environmental legislation. Full article

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 models 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 watershed, South Korea. Since TWTFM also uses SWAT model percolation output data, calibration was performed for individual models and a coupled model. The coupled model was calibrated using daily streamflow and hydraulic head. The SWAT-MODFLOW model performed well during the simulation of streamflow compared to the SWAT model. The study output showed that the study watershed had significant groundwater recharge variations during the simulated period. A significant amount of recharge happens in the wet season. It contributes a significant amount of the average annual precipitation of the region. The direct flow components (surface and lateral) showed significant 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. Full article

In the hydrology field, hydrological forecasting is regarded as one of the most challenging engineering tasks, as runoff has significant spatial–temporal variability under the influences of multiple physical factors from both climate events and human activities. As a well-known artificial intelligence tool, Gaussian process regression (GPR) possesses satisfying generalization performance but often suffers from local convergence and sensitivity to initial conditions in practice. To enhance its performance, this paper investigates the effectiveness of a hybrid GPR and cooperation search algorithm (CSA) model for forecasting nonstationary hydrological data series. The CSA approach avoids the premature convergence defect in GPR by effectively determining suitable parameter combinations in the problem space. Several traditional machine learning models are established to evaluate the validity of the proposed GPR-CSA method in three real-world hydrological stations of China. In the modeling process, statistical characteristics and expert knowledge are used to select input variables from the observed runoff data at previous periods. Different experimental results show that the developed GPR-CSA model can accurately predict nonlinear runoff and outperforms the developed traditional models in terms of various statistical indicators. Hence, a CSA-trained GPR model can provide satisfying training efficiency and robust simulation performance for runoff forecasting. Full article