River Stream Research Articles

Building cartographic models to evaluate the water quality of the Euphrates River stream extending between the Al-Shinafiya and Al-Nasiriyah cities in southern Iraq relying on GIS technology and water quality indices

هدفت الدراسة الحالية إلى تقييم نوعية مياه نهر الفرات في المنطقة الممتدة من الشنافية إلى الناصرية من خلال دراسة الخصائص النوعية للنهر ومعرفة نوعية مياهه وذلك باستخدام النموذج الكندي ( CCME WQI) والمؤشر الحسابي الموزون ، بعد ذلك تم تصنيف أصل المياه وفق طريقتي بايبر و شولير سولن ، وتبين أن جميع عناصر الخواص الفيزيائية والكيميائية عالية ، أما بالنسبة للنموذج الكندي فقد تراوحت قيم المؤشر بين (62.2-74.7)، أعلى قيمة سجلت للموقع (4)، وهو يقع ضمن المياه المقبولة ، وأقلها للموقع (1)، في حين كانت قيم (Wi*Qi) للنموذج الرياضي الموزون تراوحت بين (0.072-60.939). أعلى قيمة سجلت للخاصية (PO4) وأقلها للخاصية (TDS)، أما بالنسبة لتصنيف نوعية المياه وفق طريقة بايبر فقد تبين آن (3) من عينات مياه منطقة الدراسة تصنف على مياه أنها مياه قلوية أرضية وان الكبريتات والكلوريدات هي السائدة فيها ، آما العينات الستة الأخرى فثلاثة منها كانت نوعية المياه فيها على صورة كلوريد و الثلاثة الأخرى كانت ضمن فئة المياه الغنية بالكالسيوم ، أما حسب طريقة شولير سولن فإن جميع عينات مياه نهر الفرات هي من مجموعة الكلوريدات وتضم عائلة واحدة هي عائلة كلوريد الصوديوم .

Year-round monitoring of antibiotic-resistant bacteria in pristine uppermost stream and estimation of pollution sources

Studies on the conditions and pollution routes of antibiotic-resistant bacteria (ARB) in rivers can help provide countermeasures against the spread of ARB. This study focused on the pristine uppermost stream of a river, where Escherichia coli (E. coli) and enterococci were detected, although the stream flows through a pristine forest catchment. Antibiotic resistance of E. coli and enterococci isolated from the river water, riverbed sediment, and feces of waterside animals, such as birds and Mustelidae, were investigated throughout the year in the pristine uppermost sites. Antibiotic resistance was present in 1.4% (7/494) of the E. coli strains and 3.0% (24/812) of the enterococcal strains, and was low throughout the year. Although antibiotic resistance of bacteria isolated from feces was not detected in this watershed, the prevalence of multidrug-resistant E. coli was 0.4% (1/246) and 0.6% (1/172) in river water and riverbed sediment samples, respectively were observed. The presence of extended-spectrum β-lactamase (ESBL)-producing E. coli was confirmed in river water samples, and genomic analysis revealed that the samples possessed the CTX-M-15 group. Multidrug-resistant strains and ESBL-producing strains were classified as phylogroups B1 and A, respectively, which are E. coli phenotypes isolated from wild animals. Pulsed-field gel electrophoresis revealed analysis targeting enterococci that strains isolated from river water and bird feces were in the same cluster with 100% similarity. Therefore, bird feces are a source of enterococci in the uppermost stream of the river. Because multidrug-resistant bacteria and ESBL-producing bacteria were present in the pristine uppermost stream of the pristine river, urgent elucidation of the spreading routes of ARB is important.

Parasite Contamination of Water Source at Pangkalan Masyhur Sub-district, Medan Johor District

According to World Health Organisation (WHO) estimates, at least 1,8 billion people consume contaminated water worldwide, hence most of the diarrheal disease in the world is attributable to unsafe water, and the lack of sanitation and hygiene. Water utilization by humans and animals can generate biological pollutants which may contaminate the water. These contaminants come from waste products that may contain bacteria, protozoa, and other parasites. This was a descriptive study with cross sectional design and simple random sampling to determine the contamination of water source by pathogens, particularly parasites at Region V Pangkalan Masyhur sub-district, Medan Johor district, Medan, North Sumatera in 2012. Samples were obtained from each house, depending on the main water source used, either from tap water, open wells, or the nearby river streams. Modified Caldwell’s sedimentation technique was applied to examine the samples under light microscope. Out of the 103 water samples collected, most were from tap water (78 samples), followed by open wells (19 samples), and only six were from the nearby river streams. We found Paramecium caudatum from nine samples (8,7%) collected from the open wells and the nearby river streams, followed by hookworm larva in one tap water sample (1%). No protozoa such as Entamoeba spp., Cryptosporidium spp., and Giardia spp. found in any of the samples. Based on this data, the abundant presence of P.caudatum represented the condition of high organic debris in the open wells and the nearby river streams. Additionally, the presence of hookworm larva in the tap water indicated the distribution system was contaminated with the surrounding soil. Hence it is imperative to provide counseling about optimal environmental sanitation and clean water management, including proper maintenance for water source and its distribution system. Tap water distribution, including its network of pipe deliverance system, must be checked and maintained regularly.

Kajian Ruang Terbuka Biru Guna Menunjang Optimasi Ecosytem Services (Lokasi Kota Bandar Lampung)

One of the methods to maintain the balance of the perkotaan environment is to maintain its blue open space. There have been a lot of research on Green Open Space, but not on Blue Open Space (BOS). However, BOS also has a very important function and moreover, the ecosystem services provided by BOS can give positive implications. This research is aims to identify the existing BOS area in Bandar Lampung City. The data used in this research are Sentinel-2 satellite images for the extraction of BOS using AWEI on the Google Earth Engine platform, administrative data for the study area, field survey data for validation of the extraction results, Google Earth images for the delineation of existing BOS objects, and river stream data for the river objects of BOS. The methods used for obtaining BOS objects are machine learning-based supervised classification on Google Earth Engine, delineation, buffering, and overlay. The results of the identification of existing RTB in Bandar Lampung city are 206,01 ha consisting of embung/reservoirs, lakes, and rivers.

Microplastics meet micropollutants in a central european river stream: Adsorption of pollutants to microplastics under environmentally relevant conditions

Microplastics have emerged as pervasive pollutants in aquatic environments, and their interaction with organic contaminants poses a significant environmental challenge. This study aimed to explore the adsorption of micropollutants onto microplastics in a river, examining different plastic materials and the effect of aging on adsorption capacity. Microplastics (low-density polyethylene (LDPE), polyethylene terephthalate (PET), and polyvinyl chloride (PVC)) were introduced into a river stream, and a comprehensive analysis involving 297 organic pollutants was conducted. Passive samplers were deployed to monitor micropollutant presence in the river. Sixty-four analytes were identified in the river flow, with telmisartan being the most prevalent. Nonaged PVC showed the highest telmisartan concentration at 279 ng/g (168 ng/m2 regarding the microplastic surface), while aged PVC exhibited a fourfold decrease. Conversely, aged LDPE preferentially adsorbed metoprolol and tramadol, with concentrations increasing 12- and 3-fold, respectively, compared to nonaged LDPE. Azithromycin and clarithromycin, positively charged compounds, exhibited higher sorption to PET microplastics, regardless of aging. Diclofenac showed higher concentrations on nonaged PVC compared to aged PVC. Aging induced structural changes in microplastics, including color alterations, smaller particle production, and increased specific surface area. These changes influenced micropollutant adsorption, with hydrophobicity, dissociation constants, and the ionic form of pollutants being key factors. Aged microplastics generally showed different sorption properties. A comparison of microplastics and control sand particles indicated preferential micropollutant sorption to microplastics, underscoring their role as vectors for contaminant transport in aquatic ecosystems. Analysis of river sediment emphasized the significance of contact time in pollutant accumulation. Overall, this study provides insights into the complex interactions between microplastics and organic pollutants under environmental conditions and contributes to a better understanding of the fate and behavior of these two types of contaminants in aquatic ecosystems.

Modeling Riverbed Elevation and Bedload Tracer Transport Resting Times Using Fractional Laplace Motion

AbstractRiverbed elevations play a crucial role in sediment transport and flow resistance, making it essential to understand and quantify their effects. This knowledge is vital for various fields, including river engineering and stream ecology. Previous observations have revealed that fluctuations in the bed surface can exhibit both multifractal and monofractal behaviors. Specifically, the probability distribution function (PDF) of elevation increments may transition from Laplace (two‐sided exponential) to Gaussian with increasing scales or consistently remain Gaussian, respectively. These differences at the finest timescale lead to distinct patterns of bedload particle exchange with the bed surface, thereby influencing particle resting times and streamwise transport. In this paper, we utilize the fractional Laplace motion (FLM) model to analyze riverbed elevation series, demonstrating its capability to capture both mono‐ and multi‐fractal behaviors. Our focus is on studying the resting time distribution of bedload particles during downstream transport, with the FLM model primarily parameterized based on the Laplace distribution of increments PDF at the finest timescale. Resting times are extracted from the bed elevation series by identifying pairs of adjacent deposition and entrainment events at the same elevation. We demonstrate that in cases of insufficient data series length, the FLM model robustly estimates the tail exponent of the resting time distribution. Notably, the tail of the exceedance probability distribution of resting times is much heavier for experimental measurements displaying Laplace increments PDF at the finest scale, compared to previous studies observing Gaussian PDF for bed elevation.

Deteksi Kerawanan Banjir Genangan Menggunakan Topographic Wetness Index (TWI) di Sub Das Way Katibung

This research aims to detect flood susceptibility using the Topographic Wetness Index (TWI) and create a flood susceptibility map in the Way Katibung Sub-watershed using the Topographic Wetness Index (TWI). This study employs the Topographic Wetness Index (TWI) method with observation parameters including land slope, soil type, land elevation, rainfall, and land use. The results show that the most influential parameter on the Topographic Wetness Index (TWI) is the land slope. Therefore, TWI can be used to detect flood susceptibility in the Way Katibung Sub-watershed, which is predominantly flat. Areas with the lowest average TWI value of 6.35 have no potential for flooding, whereas areas with average TWI values of 10.94 and 13.95 are the most susceptible to flooding. The flood-prone areas are primarily located near river streams, such as Mekar Sari, Sumber Agung, Talang Way Sulan, Karang Pucung, Banjar Sari, Purwodadi, and Pamulihan in Way Sulan District. Keywords: Flood Puddle, Sub-DAS Way Katibung, TWI, Vulnerability.

Investigation of the impact of municipal solid waste disposal site leachate on surface water resources in Hosanna Town, Ethiopia.

Surface water resources are the most precious, yet they are also the most vulnerable to pollution. Consequently, maintaining the sustainability of water supplies is critical for livestock support to achieve SDG goals. Landfill leachate poses a significant threat to water resources in developing countries. This study aims to determine how the Hosanna town landfill site affects the Jewie River by analysing the quality of the Alela and Ajew streams and the landfill leachate in both wet and dry seasons. Furthermore, assess the suitability of the water quality for agricultural purposes. The leachate pollution index (LPI), Canadian Council Member of the Environment Water Quality Index (CCMEWQI), and irrigation water quality indices (IWQI) were computed for both seasons using two composite leachate samples and five flow-pace composite river samples. In the wet season, the leachate pollution indices for L1 and L2 ranged from 20.87 to 22.47, respectively. During the dry season, the leachate pollutant index of L1 and L2 was found to be 24.42 and 27.98. Only the Ajew River stream was affected during the dry season because the landfill site is only 46m away. Both the Ajew and Alela River streams are infested during the rainy season. Irrigation index concentrations revealed that the river water is suitable for cultivation. The early stages of landfill waste maturation are evident from the LPI results. Relocating the dump site is necessary to safeguard water resources because leachate has entered the river streams.

Wpływ działalności antropogenicznej w dorzeczu górnego Dunaju na reżim temperatury wody Dunaju w Bratysławie

The man activity in the basin affects the water temperature in the increasingly higher levels (construction of water reservoirs, construction of thermal and nuclear power plants or drainage of waste water to streams). In this paper, we focused our attention on the evaluation of the impact of anthropogenic activity to increase the thermal load of the Danube River for the period 1926–2020 at the Bratislava (Slovakia) station. In the first part, the long-term trends of a series of monthly and annual water temperatures in the Danube (period 1931–2020) are identified. In the second part, the dependence of the range of daily water temperature values is analysed at the temperature of the atmosphere in Vienna. The impact of an increase in the temperature of the Danube water due to human activity was tried to identify for lower, average, and higher flows (for Danube discharge at Bratislava water gauge 1500 m3s-1, 2000 m3s-1, and 3000 m3s-1) by comparing two periods: 1932–1961, and 1991–2020. As the effect of water heating in the river stream is most noticeable during low flow (dry) periods and high air temperatures, only daily water and air temperature data from the warm months between May and September were used in the calculations. At monthly flow rates of 1500 m3s-1, the water temperature was, on average, 0.5°C higher during the period of 1991–2020 than it was during the period of 1932–1960. This growth could be attributed to human activities in the Danube basin above Bratislava (warming of water in the built tanks, the wastewater flow to the Danube flow, etc.)

Design, optimization and analysis of a modified Savonius hydro-kinetic turbine (MSHT) with curved winglet and straight blade

The pico-scale power generation in remote locations is now very promising due to small-scale power requirements. The major challenge is harnessing the same from the run-off river streams or canals that have low free-stream flow-speed (less than 1 m/s). Savonius hydro-kinetic turbine can self-start in such flow streams, but it exhibits poor efficiency. This study proposes a novel airfoil-shaped curved winglet that can enhance the functionality of this turbine. The popular semi-circular blade is replaced with a hybrid blade profile consisting of a curved winglet at the front-edge, which is tore out from NACA 63415 airfoil, followed by a straight blade section up to the trailing edge, thereby resulting in a modified Savonius hydro-kinetic turbine. The curved winglet minimizes negative torque effect on the rotor, while the long straight edge offers a greater moment-arm and gap-flow. The research is performed in two stages. In the first stage, three different models of the turbine with various combinations of blade overlapping, side clearance, and winglet offset are designed. Transient Computational Fluid Dynamics (CFD) simulations are run to assess and compare the model performances under different low flow-speeds. Taguchi optimization is then performed to obtain a combination of best design and operating conditions for higher performance. In the second stage, two more design variables of the winglet, namely winglet arc angle and cut-out arc section are introduced on the previous best model and detail analysis is done to further improve the turbine performance. Finally, the two best models are compared to obtain important performance insights of the turbine. Results show that winglet parameters with best cut-out arc section and offset improve performance more than the performance with traditional overlapping or side clearance design considerations. The maximum Cp and CT of 0.36 and 0.75 are obtained for the best model at the best winglet arc angle (a1) of 30° for flow-speed 0.4 m/s, and TSR 0.7 with combinations of 20 % blade overlapping, 6.14 % side clearance, and 15 mm winglet offset. The performance parameters of the turbine is also compared with the existing modified Savonius-turbine designs to emphasize the essential improvement of the current design.

Hydrogeochemical evolution and isotopic characteristics of groundwater-surface water interaction processes within the Kawere catchment and its hydrogeotechnical implication on pit slope stability at the Nsuta mine, Ghana

In geo-hazard prone heterogenous mining terrain with multiple geological structures, surface water may interact with its underlying groundwater system conveying large quantities of water to deeper aquifers, which could undoubtedly lead to pit-inflows and slope stability challenges for any close-by mining operation. A total of forty-three (43) water samples were collected from the atmosphere, surface, subsurface and the pit-water during dry and wet seasons, respectively to identify pit-inflow origin using hydrogeochemical evolution paths and end member mixing analysis of the major ions at the only manganese mine in Nsuta, Ghana. The major ions order was Na2+>Ca2+>Mg2+>K+ for cations and anions' order was HCO3− > SO42− > Cl−. The identified hydrogeochemical facies and proportions are Ca–HCO3- (68.75%), Ca–Cl2 (18.75%) and mixed Ca–Mg–Cl (12.5%) in the dry season and mixed Ca–Na–HCO3 (54%) followed by Ca–HCO3 (46%) in the wet season. Na+ is the preeminent cation whilst HCO3− is the preeminent anion. Saturation Index (SI) of carbonate and evaporate minerals, particularly calcite, identified groundwater-surface water (GW-SW) exchange flux pathways in the study area, and thus establishing geochemical modeling as a robust tool for identifying GW-SW exchange flux pathways in riverine and aquifer systems. The isotopic composition of the various water samples is depleted having strong mixing relationship of R2 = 0.96%, suggesting the waters have same origin with low d-excess indicating rainfall under lower humidity. End member mixing analysis suggested GW-SW interaction with the surface water contributing an average of 87% to groundwater in the mine pit during the dry season. The generally low hydrogeochemical and isotopic evidence of the various water sources indicate homogeneity pointing to the existence of GW-SW interaction. The fast-movement of the exchange flux has widened flow path leading to pit slope stability issues and huge pit-inflows. Therefore, the mine managers, stakeholders, and decision makers are strongly advised to promptly integrate hydrogeotechnical assessments into their operations as a sustainable remedial measure. This will enable them to continuously reduce the potentiometric head of the groundwater system and ensure cost-efficient mining activities. It is essential to take these actions due to the mine's location within two river stream catchments.

Composition and Bioreactivity of Dissolved Organic Matter Leachates From End Members in a Mountain to Prairie Transitional River Valley

AbstractRiver organic matter transformations impact the cycling of energy, carbon, and nutrients. The delivery of distinct dissolved organic matter (DOM) sources can alter aquatic DOM cycling and associated biogeochemical processes. Yet DOM source and reactivity are not well‐defined for many river systems, including in western Canada. Here, we explore DOM cycling in the mainstem of the Oldman River (stream order 6–7), a heavily regulated river network in southern Alberta (Canada). We compared seasonal river DOM content, composition, and bioavailability with nine endmember leachates from the river valley using optical properties and incubations to estimate biodegradable dissolved organic carbon (BDOC). River DOM composition was most similar to terrestrial soil leachates, followed by autochthonous DOM leachates. River DOM bioavailability was low (BDOC = 0%–16.6%, mean of 7.1%). Endmember leachate bioavailability increased from soils (BDOC = 23.9%–53.7%), to autochthonous sources (fish excretion, macrophytes, biofilm; BDOC = 49.9%–80.0%), to terrestrial vegetation (leaves, shrubs, grass; BDOC > 80%), scaling positively with protein‐like DOM content and amount of leachable dissolved organic carbon (DOC), and negatively with aromaticity. Seasonally, DOC concentrations changed little despite >15‐fold increases in discharge during spring. River DOM composition shifted modestly toward soil‐like endmembers in spring and more bioavailable autochthonous end members in autumn and winter. Low DOM bioavailability in the river mainstem and low DOC yields shown in previous work point to limited internal processing of DOM and limited bioavailable DOM delivery to downstream habitats, possibly due to upstream flow regulation. Our observations provide important insights into the functioning of western Canadian aquatic networks.

Do Water Transfer Projects Promote Water Use Efficiency? Case Study of South-to-North Water Transfer Project in Yellow River Basin of China

With a huge capital and labor input influx, inter-basin water transfer (IBWT) projects have been shown to effectively mitigate water stress and ensure the water demand for social and economic development in the receiving area. Whether they have promoted the improvement of regional water use efficiency (WUE) is crucial for sustainable management of regional water resources. Targeting the South-to-North Water Transfer Project (SNWTP), the largest and most ambitious inter-basin water transfer project in China, this study establishes quantitatively econometric models to analyze the impact of different water diversion projects, specifically the eastern route of the SNWTP (ER-SNWTP), middle route of the SNWTP (MR-SNWTP), and diversion from the main stream of the Yellow River (DYR), on the regional water consumption per unit of GDP; regional water stress, water use structure, economic structure, and urbanization level are used as control variables in different types of cities in the Yellow River Basin, and some intriguing results are found. While the overall water transfer project demonstrates a positive impact on water use efficiency, the effects of the three water transfer measures vary significantly. The ER-SNWTP does not exhibit a notable positive effect on regional water use efficiency, whereas the MR-SNWTP demonstrates a significant positive impact. Interestingly, the DYR has a notable negative influence on water use efficiency in developed cities. The water use structure, shaped by the pricing, scale, and policies of different projects, emerges as a pivotal factor in explaining these differences. Finally, this paper suggests that the impact of water transfer projects on the improvement of regional water use efficiency be viewed from a more comprehensive and developmental perspective.

River stream flow prediction through advanced machine learning models for enhanced accuracy

The Narmada River basin, a significant water resource in central India, plays a crucial role in supporting agricultural, industrial, and domestic water supply. Effective management of this basin requires accurate streamflow forecasting, which has become increasingly important. This study delves into streamflow forecasting using historical data from five major river stations, covering the upper reaches in the East and middle sections. The dataset spans from 1978 to 2020 and undergoes rigorous screening and preparation, including normalization using StandardScaler. The research adopts a comprehensive approach, developing models for training on 70 % of historical data, validation on the most current 15 %, and testing against future targets with another 15 % of the data. To achieve precise predictions, a suite of machine learning models is employed, including CatBoost, LGBM (Light Gradient Boosting Machine), Random Forest, and XGBoost. Performance evaluation of these models relies on key indices such as mean squared error (MSE), mean absolute error (MAE), root mean square error (RMSE), root mean square percent error (RMSPE), normalized root mean squared error (NRMSE), and R-squared (R2). Notably, among these models, Random Forest emerges as the most robust for streamflow prediction, showcasing its effectiveness in handling the complexities of hydrological forecasting. This research contributes significantly to the field of streamflow forecasting in the Narmada River basin by providing insights into the performance of various machine learning models. The findings not only enhance our understanding of watershed dynamics but also highlight the pivotal role that machine learning can play in improving hydrological forecasting for sustainable watershed management.

Distribution and source of contamination of heavy metal mercury at paddy field in Mandailing Natal Regency, North Sumatera, Indonesia

Mandailing Natal Regency is administratively located in North Sumatera Province with 662,070 hectares width and a paddy field area of 40,051 hectares. Batang Gadis River stream is 180 KM long and became the source of livelihood for people in Mandailing Natal Regency as the source of drinking water, irrigation, and protein food source such as fish. Unlicensed Gold mining (PETI) occurred massively in Mandailing Natal Regency precisely at Sub-District Muara Sipongi, Sub-District Ulu Pungkut, Sub-District Huta Bargot, and Sub-District Naga Juang. The use of mercury for the amalgamation process in gold mining produces mercury waste which the run-off stream to the irrigation canals and at the end stream to Batang Gadis River Flow. This research conducted the distribution and source of contamination of heavy metal mercury at paddy fields in Mandailing Natal Regency, North Sumatera, Indonesia. The research was conducted to take soil sample analysis from paddy fields as much as 100 points from 20 paddy field locations near the amalgamation place or the water source for irrigation from Batang Gadis River that spread in five sub-districts. The soil sample analysis took for 25 cm depth. The results showed that the mercury concentration in all rice fields studied exceeded the quality standard threshold with the highest concentration found in Sub-District Naga Juang as much as 11.47 ppm followed by Sub-District Hutabargot with 10,77 ppm concentration. The factor that determines the paddy soil contamination by the mercury was the amalgamation waste which directly streams to irrigation canals compared with the paddy field with irrigation canals direct from the Batang Gadis River.

Innovative interpretable AI-guided water quality evaluation with risk adversarial analysis in river streams considering spatial-temporal effects

Water security remains a critical issue given the looming threats of industrial pollution, necessitating comprehensive assessments of water quality to address seasonal fluctuations and influential factors while formulating effective strategies for decision makers. This study introduces a novel approach for evaluating water quality within a complex riverine zone in South Korea: Han River that encompasses five river streams situated at each junction of North and South streams (including Gyeongan Stream) that ultimately leading towards Paldang Lake. By utilizing the monthly water characteristic data from the year 2013–2022 across 14 different locations, the significant seasonal trends and potential influences on water quality are identified. The water quality here is calculated with the proposed method of sub-index water quality index (s-WQI). A combinatorial prediction approach of s-WQI for each location is conducted through a collective of data preprocessing approaches including Hampel filtering and feature selection in prior to the machine learning predictions. In return, light gradient boosting (LGB) is the most accurate predictor by outperforming other prediction algorithms, especially through LGB-Pearson and LGB-Spearman combinations for North and South stream intersections, and LGB-Pearson for Paldang Lake. To further evaluate the robustness of this evaluation and extending the results to a foreseeable scenario, a seasonal based Monte-Carlo Simulation with 10,000 attempts targeting the water characteristic distributions obtained from each location considered are carried out to identify the risk bounds within. The results are further interpreted with SHAP analysis on identifying the contributions of each water characteristics towards the water quality through local and global spectrum. This research yields practical implications, offering tailored strategies for water quality enhancement and early warning systems. The integration of AI-based prediction and feature selection underscores the transformative potential of computational techniques in advancing data-driven water quality assessments, shaping the future of environmental science research.

Spatio-Temporal Variations in Nitrate Sources and Transformations in the Midstream of the Yellow River Determined Based on Nitrate Isotopes and Hydrochemical Compositions

Nitrate pollution is a major environmental problem threatening rivers, and nitrogen and oxygen isotopes have proved to be an effective means of analyzing the sources and transformations of nitrate in rivers. However, a low monitoring frequency cannot accurately reflect the changes in nitrate. In this study, the sources and transformations of nitrate in the middle reaches of the Yellow River and its tributaries during the dry season and the wet season were analyzed based on water quality parameters and nitrate isotopes. Stable isotope analysis conducted using the R (SIAR) model was used to estimate the proportions of different nitrate sources. The results showed that the main nitrate sources in the main stream were soil nitrogen (40.95–45.83%) and domestic sewage and manure (30.93–32.60%), respectively, with little variation between the dry season and wet season because of the large flow of the Yellow River. During the dry season, the nitrate sources of the two tributaries were mainly domestic sewage and manure (45.23–47.40%), followed by soil nitrogen (31.35–34.00%). However, the primary nitrate source of T2 (Qin River) became soil nitrogen (40.05%) during the wet season, a phenomenon that was mainly caused by the significant increase in river discharge and in soil erosion in the basin. During the wet season, the concentrations of total nitrogen (TN) and nitrate (NO3−) significantly decreased in the main stream and tributaries, and nitrification and denitrification processes occurred in both the main stream and tributaries of the Yellow River. In addition, the T2 tributary (Qin River) was also significantly affected by mixed dilution. High-frequency sampling can reflect the isotopic information of nitrate in the river more comprehensively, which helps us to understand the conversion process of nitrate more accurately.

Spatiotemporal patterns of water volume and total organic carbon concentration of agricultural reservoirs over South Korea

Lacking of available water quality data causes the limited understanding of the coupled dynamics of hydrologic and nutrient cycles in lakes and reservoirs and along river streams. This study conducts the rotated Principal Component Analysis (rPCA) of water volume and total organic carbon (TOC) concentration data from ∼2200 agricultural reservoirs in South Korea to extract the major modes of their spatiotemporal variability. Over 2020–2022, the total TOC load in the reservoirs ranges between 1,165 and 1,492 tons (289 and 360 Mtons of water storage volume; 3.54 and 4.60 mg/L of TOC concentration). The first rPCA mode is assoicated with a decreasing trend of water level (38 % of the explained variance) and increasing trend of TOC concentration (27 %) over the southern Korea region, where the TOC concentration increased during the 2022 drought. The second rPCA mode is associated with interannual variability of water level (25 %) and TOC concentration (18 %) over the central Korea region. This study found a marginal relationship between paddy field area and TOC concentration and their regime shift to high TOC concentration during the 2022 drought, which was a potential cause of the increased TOC concentration in 2022. This study provided observational evidence of interactions between water volume and TOC concentration during a severe drought, suggesting a possible shift of the role of agricultural reservoirs to carbon source.

A novel machine learning-based framework for the water quality parameters prediction using hybrid long short-term memory and locally weighted scatterplot smoothing methods

ABSTRACT Water quality prediction is crucial for effective river stream management. Dissolved oxygen, conductivity and chemical oxygen demand are vital chemical parameters for water quality. Development of machine learning (ML) and deep learning (DL) methods made them widely used in this domain. Sophisticated DL techniques, especially long short-term memory (LSTM) networks, are required for accurate, real-time multistep prediction. LSTM networks are effective in predicting water quality due to their ability to handle long-term dependencies in sequential data. We propose a novel hybrid approach for water quality parameters prediction combining DL with data smoothing method. The Sava river at the Jamena hydrological station serves as a case study. Our workflow uses LSTM networks alongside LOcally WEighted Scatterplot Smoothing (LOWESS) technique for data filtering. For comparison, Support Vector Regressor (SVR) is used as the baseline method. Performance is evaluated using Root Mean Squared Error (RMSE) and Coefficient of Determination R2 metrics. Results demonstrate that LSTM outperforms the baseline method, with an R2 up to 0.9998 and RMSE of 0.0230 on the test set for dissolved oxygen. Over a 5-day prediction period, our approach achieves R2 of 0.9912 and RMSE of 0.1610 confirming it as a reliable method for water quality multistep parameters prediction.

Long-term and combined heavy-metal contamination forms a unique microbiome and resistome: A case study in a Yellow River tributary sediments

Microorganisms have developed mechanisms to adapt to environmental stress, but how microbial communities adapt to long-term and combined heavy-metal contamination under natural environmental conditions remains unclear. Specifically, this study analyzed the characteristics of heavy metal composition, microbial community, and heavy metal resistance genes (MRGs) in sediments along Mang River, a tributary of the Yellow River, which has been heavily polluted by industrial production for more than 40 years. The results showed that the concentrations of Cr, Zn, Pb, Cu and As in most sediments were higher than the ambient background values. Bringing the heavy metals speciation and concentration into the risk evaluation method, two-thirds of the sediment samples were at or above the moderate risk level, and the ecological risk of combined heavy metals in the sediments decreased along the river stream. The high ecological risk of heavy metals affected the microbial community structure, metabolic pathways and MRG distribution. The formation of a HM-resistant microbiome possibly occurred through the spread of insertion sequences (ISs) carrying multiple MRGs, the types of ISs carrying MRGs outnumber those of plasmids, and the quantity of MRGs on ISs is also higher than that on plasmids. These findings could improve our understanding of the adaptation mechanism of microbial communities to long-term combined heavy metal contamination.