Surface Water Levels Research Articles

Assessing the Spatio-Temporal Variability in the Frequency and Magnitude of Flash Floods and their Driving Mechanisms: Evidence from Haor Region of Bangladesh

There are a limited number of studies addressing the spatiotemporal variability of pre-monsoon flash floods and their driving forces in Bangladesh. This study examines long-term trends in temperature, rainfall, and the frequency and magnitude of flash floods in the five most vulnerable haor districts of northeastern Bangladesh. Temperature, rainfall, and surface water level datasets, up to 2018, were collected from the Bangladesh Meteorological Department (BMD) and the Bangladesh Water Development Board (BWDB). Based on the normal distribution of these datasets observed in quantile-quantile (Q-Q) plots, regression models were used to analyze the long-term temperature trends. The models predict a gradual rise in maximum temperature, ranging from 1.06% to 1.94% over decadal periods. Additionally, an average annual rainfall increase of 4.1% at Sreemangal and 2.28% at Sylhet stations are forecasted. Analysis of historical data from the past sixty years shows a relatively lower peak river stage in tidal rivers compared to non-tidal river stations during pre-monsoon months. The frequency of peak surface water levels at six non-tidal and ten tidal river monitoring stations was estimated using Gumbel's probability estimation method. Frequency analysis suggests a high probability of flash floods across most floodplain areas, with a return period of five to ten years, based on flood danger levels established by government agencies. Furthermore, MODIS satellite imagery (with cloud cover <10%) from the peak flood months (March to May) between 2004 and 2017 was analyzed to assess the extent of flash floods in the study area. Geospatial analysis revealed temporal variations in peak flood extents across different locations. While no clear trends were observed in the frequency of flash floods, their magnitude has significantly increased in recent decades, potentially leading to greater losses in agriculture and property. The increased vulnerability to flash floods in the region can be attributed to several factors, including a rise in pre-monsoon heavy rainfall in the upstream hilly regions of Assam and Meghalaya, high sediment loads in Transboundary Rivers, drainage congestion, poorly designed and maintained flood control structures, and the absence of a reliable flash flood warning system. J. Asiat. Soc. Bangladesh, Sci. 50(1-2): 33-50, June-December 2024

Impacts of Time‐to‐Freeze on Quality Attributes of Low‐Moisture Part‐Skim Mozzarella Cheese

ABSTRACTThis research investigated the effect of time‐to‐freeze (TTF) on key quality attributes of low‐moisture part‐skim (LMPS) Mozzarella cheese, including browning, free oil formation and meltability. Thin slabs (4‐mm) of LMPS Mozzarella were frozen at four different rates: in a still air freezer (−22°C), in a non‐isothermal blast freezer (−30°C), in a temperature‐controlled bath (−30°C), and in an ethanol‐dry ice bath (−70°C), with TTF ranging from 0.4 to 95 min. Numerical simulations of the transient heat conduction equation provided temperature profiles that were compared with the experimental data for all freezing methods. Frozen samples were stored at −22°C for 15–18 h, then thawed and analyzed for browning, free oil formation, and meltability using spectrophotometry and modified Schreiber tests. TTF variations did not significantly affect the quality attributes, but samples with a TTF of 95 min had higher levels of free surface water compared to unfrozen cheese. The formation of free surface oil increased significantly after TTF durations of 1.2, 19, and 95 min compared to unfrozen samples. Surface browning decreased after 95 min, likely due to the higher free water content. Rapid freezing methods, such as the ethanol‐dry ice bath (−70°C), are effective for quick freezing, but the still air freezer yielded better quality cheese. Cheese frozen in a still air freezer exhibited less redness (a*) and more lightness (L*), indicating reduced surface browning. Additionally, it retained more free surface water, enhancing the structural integrity and overall quality of LMPS Mozzarella.

Urban stormwater discharge contributes more micropollutants to surface water in humid regions of China: Comparison with treated wastewater.

Micropollutants have raised increasing concern due to their adverse effect on ecosystems and human health. So far, the effects of micropollutants in urban stormwater discharge on surface water quality or ecosystem health remains unclear. In this study, target and non-target screening methods were used to quantify and identify micropollutants in urban stormwater, wastewater, and surface water in humid regions of China. Results showed that the average concentration of micropollutants in surface waters in wet weather was 1.8 times that in dry weather. The cumulative concentrations of 143 micropollutants in samples from stormwater discharge were in the range of 490-1659 ng/L, which were comparable to or exceeded those from wastewater discharge. In terms of mass load in the studying area, stormwater discharges contained 10.8 kg of micropollutants in the month, a higher level compared to 4.58 kg in treated wastewater. Furthermore, the calculated risk quotients revealed medium to high ecological risk to aquatic organisms from substances such as telmisartan, irbesartan, 1,7-dimethylxanthine, and caffeine at ng/L concentrations, which are in typical levels in urban stormwater and surface waters in wet weathers. Our study reveals that urban stormwater discharge is an important pathway for micropollutants to surface waters, and urges for increased emphasis on, and reinforcement of, urban stormwater monitoring and control measures to minimize the transport of micropollutants to receiving waterbodies.

The impact of dam management and rainfall patterns on flooding in the Niger Delta: using Sentinel-1 SAR data

This study explored how dam operation and rainfall patterns interact to influence flooding in the Niger Delta, Nigeria. This study utilizes Sentinel-1 Synthetic Aperture Radar (SAR) data to analyze the flood events from 2018 to 2022, focusing on key locations such as Obiafu (downstream), Kainji/Jebba, and Lagdo dams (upstream). Analyzed Sentinel-1 satellite data [European Space Agency (ESA), 2018–2022], shuttle Radar Topography Mission, alongside rainfall data [Center for Hydrometeorology and Remote Sensing (CHRS), 2018–2022] and surface water level to assess flood variations between 2018 and 2022. The flood extent was differentiated from that of permanent water bodies using Sentinel-1 images with an RGB band (Snap 7.0), and the rainfall patterns were examined via inverse distance weighting (IDW) interpolation (ArcGIS 10.5). The findings reveal that the intensity and timing of flooding vary significantly across these regions. Obiafu experienced high flooding in October 2020 and 2022, while Kainji/Jebba and Lagdo dams had contrasting flood severities during these periods. Additionally, a comparative analysis of hydrograph data from these locations shows a delayed downstream response, highlighting the need for coordinated water release strategies to mitigate flood risks. The results also indicate that upstream dam operations, particularly water releases, contribute to downstream flooding, although local rainfall patterns remain a crucial factor. By aligning SAR data with real-time water levels, this study emphasizes the importance of integrating satellite-based monitoring with hydrological models to improve flood prediction accuracy and minimize socio-economic impacts in the Niger Delta. The study concludes that enhanced flood management strategies, incorporating both rainfall forecasting and dam operation schedules, are critical for reducing flood-related vulnerabilities in the region.

Molybdenum Disulfide/Diselenide-Laser-Induced Graphene-Glycine Oxidase Composite for Electrochemical Sensing of Glyphosate.

The widespread use of the pesticide glyphosate has raised concerns regarding its potential health and environmental impacts. Consequently, there is an increasing demand for monitoring glyphosate levels in surface waters and food products. Currently, there is no commercially available rapid, field-deployable sensor capable of quantifying glyphosate concentrations in environmental samples. This study presents the development of a biosensor based on laser-induced graphene (LIG) that is functionalized with transition metal dichalcogenides (TMDs) and the enzyme glycine oxidase. The LIG is created through a scalable process using a CO2 laser to convert polyimide into a porous, nano/microstructured graphene architecture. The high surface area of LIG acts as a conductive scaffold for subsequent functionalization of both molybdenum disulfide (MoS2) and molybdenum diselenide (MoSe2) to further improve the electroactive surface area of the electrode. The resultant sensors, functionalizesd with the enzyme, demonstrate linear sensing ranges from 10 to 90 μM for glyphosate with detection limits of 4.0 and 6.1 μM for LIG electrodes modified with MoS2 and MoSe2, respectively. Furthermore, the sensors detect glyphosphate at negative working potentials, helping to minimize interference from endogeneous electroactive species and to provide consistent glyphosphate monitoring in actual food products (i.e., soybeans and pinto beans). Overall, the biosensors integrate scalable manufacturing with cost-effective TMDs and LIG, eliminating the need for costly noble metals in the biosensor design, and offering a reliable method for assessing glyphosate in food products.

Pollution of water bodies and related impacts on aquatic ecosystems and ecosystem services: the case of Ghana’s booming ‘galamsey’ industry

Galamsey is a Ghanaian jargon from the phrase “gather and sell,” coined from how gold was mined with simple tools by natives and sold afterwards, is deeply rooted in culture. Despite its socio-economic benefits, a significant upsurge in galamsey has been widely associated with significant environmental impacts viz, destruction of aquatic ecosystems and ecosystems services. This paper discuses impacts of galamsey on aquatic ecosystems and ecosystem services using the Driver-Pressure-State-Impact-Response framework in combination with the quantitative defensible impact characterization approach to establish the cause-and-impact relationships between pollutants associated with galamsey, the extent to which aquatic ecosystems and ecosystem services are impacted while answering the questions what is happening to the environment and why it is happening (compilation and analysis of status and trends of key environmental indicators) and what the consequences are for the environment (analysis of impacts of environmental change on ecosystem services). There were highly significant differences (P<0001) between the analysed mean Hg, As and turbidity levels and the permissible levels in surface water with the potential of affecting ecosystem services including water for drinking, water for recreational, water for irrigational, and water for aqua culture purposes. Spiritual values, symbolic values, recreation, aqua culture and fish harvest were among ecosystem services highly impacted with a high impact significance ranged 101-125 (++++orange) while aesthetic experience was very highly impacted with a very high impact significance ranged between 126-150 (+++++red). Discolouration by silt, and hydromorphological alteration had a medium-high impact significance ranged from 76-100 (+++yellow) while spiritual value had a low-medium impact significance ranged from 51-75 (represented by ++green). It is recommended that efforts are made to promote responsible cleaner operations in the artisanal and small-scale gold mining sector through the provision of subsidized eco-friendly tools for gold amalgamation in addition to regular capacity building training on the impacts of galamsey on ecosystems, ecosystem services and human health using cycle of cause-effect-outlook relationship.

Flooding and elevated prenatal depression in a climate-sensitive community in rural Bangladesh: a mixed methods study.

Prenatal depression can have lasting adverse impacts on child health. Little is known about the impact of floods on prenatal depression in low- and middle-income countries. We conducted a cross-sectional survey of 881 pregnant women from September 24, 2023 to July 19, 2024 in riverine communities in rural Bangladesh. We recorded participant-reported flooding in the past 6 months, administered the Edinburgh Postnatal Depression Scale (EPDS), and obtained water level data and remote sensing data on distance to surface water. We fit generalized linear and log-linear models adjusting for month, wealth, education, age, and gestational age. We conducted 2 focus group discussions with 20 adult women. 3.6% of compounds were flooded in the past 6 months. Compound flooding was associated with elevated depression (adjusted prevalence ratio (aPR) = 2.08, 95% CI 1.14, 3.51) and thoughts of self-harm (aPR=8.40, 95% CI 4.19, 16.10). Latrine flooding was associated with higher depression (aPR=3.58, 95% CI 1.49, 7.29)). Higher water levels and shorter distance to permanent surface water were significantly associated with mean EPDS scores. Focus groups revealed that domestic violence, inadequate sanitation, gendered vulnerabilities in accessing latrines, childcare difficulties, and food insecurity were key drivers of depression due to floods. Flood preparedness strategies included relocation, storing food, and home modifications. Flooding, higher water levels, and proximity to water bodies were associated with prenatal depression in a rural, low-income setting. Inadequate sanitation and hygiene infrastructure were particularly strong drivers of depression. Eunice Kennedy Shriver National Institute of Child Health and Human Development. Evidence before this study: We searched SCOPUS titles, abstracts, and keywords as follows: (antenatal OR prenatal OR perinatal OR prepartum OR pregnan* OR antepartum OR maternal) AND (depress* OR "mental health") AND (flood*). After filtering to include research articles focused on humans, we identified 35 articles, including 3 protocols, 4 reviews, 22 research articles in high-income settings, and 7 research articles in low- or middle-income countries (LMICs).In high-income settings, two studies have found that flooding is associated with prenatal depression. A review of the influence of extreme weather events on maternal health in LMICs only found one study that investigated the relationship between flooding and mental health (specifically coping) in pregnancy, but it did not measure depression. The search did not yield any studies that have investigated the relationship between flooding and prenatal depression in LMICs.Added value of this study: To our knowledge, this is the first study estimating the association between flooding and prenatal depression in an LMIC. In a cross-sectional survey in a flood-prone region of rural Bangladesh, we found that flooding of the household compound and latrine was associated with higher prenatal depression prevalence. Proximity to surface water and higher water levels were associated with higher Edinburgh Postnatal Depression Scale scores. Our study describes flood preparedness strategies used by pregnant women and their households to inform climate adaptation in rural, riverine communities. We observed that these strategies largely focused on short-term mitigation rather than long-term resilience as more than half of all strategies involved temporary relocation.Additionally, we qualitatively examined gender-specific vulnerabilities related to flooding to understand mechanisms through which flooding may contribute to prenatal depression, with the aim of informing targeted flood resilience interventions for pregnant women. Women reported increased domestic violence during floods, gendered vulnerabilities in accessing latrines, and childcare difficulties, and food insecurity during floods.Implications of all the available evidence: Our findings underscore the need to integrate maternal mental health care into climate resilience policy in flood-prone regions to prevent adverse downstream effects on child development and birth outcomes. Though pregnant women described multiple adaptation approaches, strong associations between flooding and depression indicate that existing adaptation methods fall short of supporting climate-related resilience. Climate-resilient water, sanitation, and hygiene (WASH) infrastructure may be particularly important to prenatal mental health during floods. Interventions may be most effective if targeted to women residing in areas closest to surface water.

Application of Photocatalytic Ozonation for the Remediation of Aquaculture Effluents: A Review

The growing global population and limitations in fish catch production have led to a surge in the demand for aquaculture. Contaminants of emerging concern (CEC) are frequently being detected at low levels in surface water. These CECs, which include previously unidentified or unregulated pollutants, pose potential risks to health and the environment, though their impacts are not yet fully understood. Extensive research studies have been proposed and undertaken to address the issue of aquaculture wastewater, aiming to minimize its impact and implement effective treatment methods. This review provides an analysis of various technologies used for treating aquaculture wastewater using advanced oxidation processes (AOPs) focusing on photocatalysis and ozonation. It examines their advantages and disadvantages, as well as their respective treatment efficacies, and discusses their potential applications in sustainable aquaculture practices complying with the Sustainable Development Goals of 1, 2, and 6 as well as being in line with the Environmental Social and Governance (ESG) framework.

Water Level Sensor Berbasis Arduino UNO R3

The availability of clean water is essential in daily life and plays an important role in agriculture, industry, and households. Water resource management faces many challenges such as fluctuations that can cause waste and shortages. The purpose of this research is to create a device that can automatically monitor water surface levels. The tool in question is a water level sensor based on Arduino Uno, which consists of a water level sensor and an Arduino Uno microcontroller. The sensor technology on Arduino can effectively monitor water usage directly and is known for its ease of use, flexibility, and sensor compatibility. An efficient water monitoring system provides accurate information about water availability.

Removal of As(V) and Cr(VI) using quinoxaline chitosan schiff base: synthesis, characterization and adsorption mechanism

Elevated Arsenic and Chromium levels in surface and ground waters are a significant health concern in several parts of the world. Chitosan quinoxaline Schiff base (CsQ) and cross-linked chitosan quinoxaline Schiff base (CsQG) were prepared to adsorb both Arsenate [As(V)] and Chromium [Cr(VI)] ions. The thermo-gravimetric analysis (TGA), X-ray diffraction analysis (XRD), and Fourier-transform infrared spectroscopy (FTIR) were used to investigate the prepared Schiff bases (CsQ) and (CsQG). The UV–VIS spectra showed a shift in the wavelength area of the modified polymer, indicating the reaction occurrence, besides the variation of the shape and intensity of the peaks. The XRD patterns showed the incensement of the amorphous characteristic. On the other hand, the thermal stability of the modified polymers is better according to TGA studies; also, the morphology of the modified chitosan was investigated before and after crosslinking (CsQ and CsQG) using a scanning electron microscope (SEM) where the surface was fall of wrinkles and pores, which then were decreased after cross-linking. Contact time, temperature, pH, and initial metal ion concentration were all studied as factors influencing metal ion uptake behavior. The Langmuir, Temkin, Dubinin–Radushkevich, and Freundlich isotherm models were used to describe the equilibrium data using metal concentrations of 10–1000 mg/L at pH = 7 and 1 g of adsorbent. The pseudo-first-order and pseudo-second-order kinetic parameters were evaluated. The experimental data revealed that the adsorption kinetics follow the mechanism of the pseudo-second-order equation with R2 values (0.9969, 0.9061) in case of using CsQ and R2 values (0.9989, 0.9999) in case of using CsQG, demonstrating chemical sorption is the rate-limiting step of the adsorption mechanism. Comparing the adsorption efficiency of the synthesized Schiff base and the cross-linked one, it was found that CsQ is a better adsorbent than CsQG in both cases of As(V) and Cr(VI) removal. This means that cross-linking doesn’t enhance the efficiency as expected, but on the contrary, in some cases, it decreases the removal. In addition, the newly modified chitosan polymers work better in As(V) removal than Cr(VI); the removal is 22.33% for Cr(VI) and 98.36% for As(V) using CsQ polymer, whereas using CsQG, the values are 6.20% and 91.75% respectively. On the other hand, the maximum adsorption capacity (Qm) for As(V) and Cr(VI) are 8.811 and 3.003 mg/g, respectively, using CsQ, while in the case of using CsQG, the Qm value reaches 31.95 mg/g for As(V), and 103.09 mg/g for Cr(VI).

Spatiotemporal distributions, sources, and health risks of heavy metals in an acid mine drainage (AMD)-contaminated karst river in southwest China

Acid mine drainage (AMD), characterized by its acidity and high content of heavy metals, is a significant global environmental problem that harms human health through its impact on rivers. Therefore, this study aims to identify heavy metals in both surface and underground AMD-polluted karst rivers, focusing on the Zhijin River area which is severely affected by AMD, and assess their health risks to residents. Through the collection of 30 surface water samples and 16 groundwater samples from both wet and dry seasons, the study examines the concentration, sources of pollution, and health implications of six heavy metals (Fe, Mn, Cr, Cd, As, and Hg). The results showed that Fe and Mn levels in surface water were highly polluted during both seasons, especially during the wet season, with Fe levels reaching 20.0 mg/L and Mn levels reaching 1.9 mg/L. Further correlation and principal component analyses revealed that mining activities are the primary contributors to the contamination in this region. Health risk assessments and Monte Carlo simulation, including both deterministic and probabilistic, showed that the noncarcinogenic health risk indices for surface water and groundwater were within acceptable limits for both seasons. However, groundwater poses a higher carcinogenic risk to children, with As levels during the wet season and Cr levels during the dry season warranting close monitoring. Factors such as body weight and intake rate played a crucial role in health risk evaluations. This study underscores the need for further attention to groundwater risk, temporal heterogeneity in the Zhijin River.

A high-performance ray tracing particle tracking model for the simulation of microplastics in inland and coastal aquatic environments

In this study, we present a high-performance Particle Tracking Model (PTM) designed for simulating any type of particles, with a focus on microplastics. The PTM is efficient compared to existing models, parallelized, and utilizes a ray tracing algorithm incorporating both ray reflection and ray refraction in order to traverse particles as well as find the location of each particle over three-dimensional unstructured grids. Various numerical corrections are implemented in the model to address computational round-off errors and discontinuities in the water surface level of the input hydrodynamic models. To increase the accuracy of the model, partially reflective boundary conditions are imposed as well as the capability to simulate microplastics beaching and washout in very shallow areas or dry computational cells. Several tests are conducted to study the performance, scalability, and accuracy of the model. The proposed model is tested with over 3.88 billion double-precision particles on three-dimensional computational grids with up to approximately one million cells. The tests show that the ray tracing approach is efficient, achieves over 17× faster runtime, and offers greater accuracy compared to using an auxiliary grid for particle location finding. For larger timesteps, the ray tracing PTM with refraction shows improved accuracy compared to the ray tracing PTM without refraction. The model's capabilities are tested in a real-world case study over the Saguenay Fjord, Quebec, Canada. The model is utilized to reproduce the paths of five surface drifters. A second numerical test is conducted in the Fjord and high particle concentration areas are identified.

Automated Monitoring System for Rainwater Harvesting Tank at Telkom University

The use of ground tank constructed by Telkom University for Rainwater Harvesting (RWH), is limited to environmental maintenance due to concerns regarding the quality of water in the underground tank. Therefore, this research aims to develop a remote monitoring device that uses Internet of Things (IoT) technology to monitor the pH, water surface, submerged materials, and water clarity levels in ground tank. To achieve the requirements, pH, ultrasonic-based volume, Total Dissolved Solids (TDS), and Turbidity sensors were selected due to the IoT connectivity. The enabling device, namely the ESP 32 microcontroller and Blynk platform were installed on monitoring dashboard on a tablet computer with 4GB of RAM. The result showed that calibration of each sensor had good accuracy, except for the Turbidity sensor due unavailable materials. In conclusion, the RWH monitoring system is suitable for use.

Linking fish bioturbation to life history in a eutrophic wetland: An analysis of fish contributions to internal nutrient loading

Abstract Bioturbation (sediment disturbance by animal actions) effects on nutrient cycling and nutrient levels in surface waters are difficult to quantify, in part because the diversity and magnitude of species‐specific influences are poorly understood. These influences may have consequences for the management of the trophic state of freshwater ecosystems. Fish cause bioturbation in freshwater and marine ecosystems by digging in benthic sediments, manipulating periphyton mats while searching for prey and scraping hard substrates while feeding. We used experimental enclosures (2.25 m2) to quantify bioturbation‐mediated phosphorus (P) and nitrogen (N) regeneration from sediment by three species of fish that differ in interactions with the benthos (largemouth bass, Micropterus salmoides; tilapia, Oreochromis spp.; and sailfin catfish, Pterogoplichthys spp.) in shallow eutrophic wetlands in Southern Florida. Tilapia are omnivores that include detritus in their diet (winnowing or ingesting sediments) and dig nests in soft sediments year round, sailfin catfish actively burrow into substrate and consume detritus (digging and ingesting sediments), and largemouth bass are piscivores that do not routinely interact with the benthos when feeding but may dig nests in soft sediment in spawning season (January–April). We quantified the amount of suspended flocculent organic matter and changes in water column nutrients (total phosphorus [TP] and total nitrogen [TN]) in 2‐week trials for each species and estimated the portion of nutrient increases relative to fishless controls that could be attributed to bioturbation‐mediated internal nutrient loading through suspension of organic matter (as opposed to excretion or other sources of nutrient loading). Water column nutrient concentrations increased with increasing biomass for all species, but the bioturbation contribution differed by species. Largemouth bass increased water column nutrient concentrations (TP: 86% and TN: 5% relative to controls) but did not influence water column suspended particulate matter through bioturbation of sediment. Tilapia increased water column nutrients a modest amount (TP: 8%; TN: 15%), of which a small portion was attributed to bioturbation (c. 18% of TP). Sailfin catfish raised water column nutrients substantially (TP: 105%; TN: 46%) and up to 100% of the increased TP was attributed to bioturbation. Sailfin catfish also suppressed algal growth and TP accumulation on the sides of the enclosures and reduced nutrient concentrations of the flocculent sediments. Our results were consistent with our hypothesis that behaviour and foraging traits affect bioturbation contributions to nutrient loading. The results also demonstrated that species with similar net effects like largemouth bass and sailfin catfish, added nutrients via different mechanisms (i.e. excretion vs. bioturbation). Considering the feeding strategies and interactions with the substrate of common fish species may assist managers in meeting nutrient reduction goals for eutrophic wetlands and managed freshwater systems.

Groundwater-surface water exchanges in an alluvial plain in southern France subjected to pumping: A coupled multitracer and modeling approach

Study regionThe study was conducted in an alluvial plain between the Rhône and the Ouvèze Rivers (in the southeast of France) extensively exploited for drinking water. The research area is characterized by significant groundwater-surface interactions influenced by groundwater pumping activities. Study focusThe aim of this study is to enhance the understanding of interactions between rivers and alluvial aquifers by combined multi-tracer and numerical modeling approaches. Over an 18-month period, groundwater temperature, piezometric levels, and river surface water levels were continuously monitored. Field campaigns focused on conductivity, stable isotopes of water, and radon-222 activity concentration in both groundwater and surface water. Radon-222 was used to quantify water exchanges between the river and the aquifer. A MODFLOW model, calibrated using piezometric data and PEST, was employed to simulate groundwater flow and reactive transport of radon-222 using MT3DMS. New hydrological insights for the regionThe study reveals that river water recharges the aquifer, with radon-222 data delineating this recharge zone. The methodology extended the interpretation of periodic groundwater temperature signals to isotopic signals, allowing the identification of dispersivity and Darcy's velocity. The Ouvèze River was found to contribute approximately 55 % of the pumping water supply, alongside the Rhône. These findings provide valuable insights for sustainable water resource management, demonstrating the relevance of using natural tracers in scenarios where artificial tracers are impractical.

Estimation of Surface Water Level in Coal Mining Subsidence Area with GNSS RTK and GNSS-IR

Ground subsidence caused by underground coalmining result in the formation of ponding water on the ground surface. Monitoring the surface water level is crucial for studying the hydrologic cycle in mining areas. In this paper, we propose a combined technique using Global Navigation Satellite System Real-Time Kinematic (GNSS RTK) and GNSS Interferometric Reflectometry (GNSS-IR) to estimate the surface water level in areas of ground subsidence caused by underground coal mining. GNSS RTK is used to measure the geodetic height of the GNSS antenna, which is then converted into the normal height using the local height anomaly model. GNSS-IR is employed to estimate the height from the water surface to the GNSS antenna (or, the reflector height). To enhance the accuracy of the reflector height estimation, a weighted average model has been developed. This model is based on the coefficient of determination of the signal fitted by the Lomb-Scargle spectrogram and can be utilized to combine the reflector height estimations derived from multiple GNSS system and band reflection signals. By subtracting the GNSS-IR reflector height from the GNSS RTK-based normal height, the proposed method-based surface water level estimation can be obtained. In an experimental campaign, a low-cost GNSS receiver was utilized for the collection of dual-frequency observations over a period of 60 days. The collected GNSS observations were used to test the method presented in this paper. The experimental campaign demonstrates a good agreement between the surface water level estimations derived from the method presented in this paper and the reference observations.

Potential phosphorus mobilization from riparian vegetation following freezing

Phosphorus (P) rich runoff from agricultural landscapes is a major contributor to freshwater eutrophication. Vegetated riparian zones are often employed to retain P from field runoff before it enters streams. In cold regions, vegetation has the potential to release P to runoff following freezing; however, it is unclear if this differs with winter frost severity, riparian zone local topography, vegetation type, and/or exposure to flooding/inundation. To explore the vulnerability of riparian vegetation to winter P losses, this study quantified soil and vegetation P concentrations from 8 riparian zones in Canada at different topographic positions within each riparian site (upper/field edge, lower/water edge) in both the fall and spring seasons and related this to observed surface temperatures and water levels throughout the non-growing season. This was complemented by two laboratory mesocosm experiments in which (1) plant samples were subjected to moderate (−40C) and severe (−250C) simulated winter frost treatments to quantify changes in their water extractable P (WEP) content, and (2) mesocosms were inundated with water to determine if dissolved P concentrations in flood water differed when plants were left intact, clipped but left on the soil surface, or harvested. Greater soil and vegetation P concentrations were observed at upper locations (field edge), and this remained consistent following freezing; however, vegetation WEP concentrations increased with greater simulated frost severity. In the field, temperatures were moderated by snow cover and although differences with riparian zone position were apparent between fall and spring collected samples, changes in P pools did not appear to be related to frost severity or inundation in the field. The mesocosm experiment revealed that harvesting vegetation considerably reduced dissolved P concentrations in flood water. This study shows that vegetated riparian zones can act as a source of P to streams during the winter non-growing season, and highlights the potential for riparian vegetation management in reducing P losses from riparian zones in cold climates.

Investigations on the removal of phosphate and nitrate using a mixture of cactus and Moringa seed powder via RSM techniques

Humans utilize water for a variety of purposes, which needs the treatment. The study explores the use of blended cactus and Moringa seed powder as coagulants to reduce phosphate and nitrate levels in surface water. Samples was collected from the Kitto River in the Oromiya region, Jimma, Ethiopia, were analyzed using various tools. A jar test was used to investigate the study using blended powder of cactus and Moringa under different operating parameters. In this study, pH (5−9), settling time (30–50 min), stirring speed (40–50 rpm), and dosage ratio (50 %C to 50 %M, 25 % C to 75 %M, and 75 % C to 25 % M) were used to analyze the removal % of NO3-, and PO43-. The highest removal efficiency was achieved with a dosage ratio of 3 (75 % M: 25 % C), a pH of 7, a settling time between 40 to 50 min, and a stirring speed of less than 50 rpm. The removal efficiencies closely matched the predicted values (92.6 %, 88.31 %) and actual values (99.46 %, 92.32 %) for PO43- and NO3- respectively. Hence, the finding showed that blended cactus with Moringa seed increases the effectiveness of phosphate and nitrate reduction.

Application of machine learning models in predicting discharge coefficient of side B-type piano key weir

Side weir is a hydraulic structure within a channel which is usually used to discharge excess water, to divert the flow, and to regulate water surface levels in rivers and irrigation and drainage networks. In general, piano key weirs (PKW) have been used as weirs perpendicular to the flow direction in straight channels. However, the use of the PKW as a side weir in the outer arch of the channels is a new approach to enhance the weir's performance. In this study, 289 tests were first performed on the B-type rectangular side piano key weir (RSPKW) at two arc angles of 30 and 120°. Then, Fuzzy Inference System (FIS), Adaptive Neuro-Fuzzy Inference System (ANFIS), ANFIS and Teaching Learning Based Optimization (TLBO), ANFIS and Grasshopper Optimization Algorithm (GOA), Extreme Learning Machine (ELM) and Outlier Robust ELM (ORELM) models were used to predict the weir discharge coefficient. The results showed that two optimization models of TLBO and GOA increased the accuracy of the ANFIS model. The results showed that the ANFIS-GOA model has accuracy of Root Mean Squared Error (RMSE) = 0.0361, Coefficient of determination (R2) = 0.9772, and Kling Gupta coefficient (KGE) = 0.9858. The ANFIS-TLBO, ANFIS, and FIS models were ranked, respectively. Also, the results showed that ELM and ORELM models have accuracy close to ANFIS-GOA and can be a suitable alternative for complex fuzzy models. According to the statistical analysis, it was found that the parameters of the ratio of weir height to flow depth at the upstream edge of weir (P/h1), arc angle (α), and the ratio of height of the foundation to the main channel width (pd/B) had the greatest role in the development of the models, respectively.

Khảo sát hiện trạng ô nhiễm vi nhựa trong nước mặt và trầm tích tại lưu vực sông Tiền, đồng bằng sông Cửu Long, Việt Nam

This study evaluated microplastic levels in surface water and sediment in Tien River basin (a branch of the Mekong River flowing through Vietnam). Water and sediment samples was taken at 18 sites along the Tien River basin. Samples was treated base on the Fenton reactions (H2O2/Fe2 ) and the density separation with ZnCl2. The results show that microplastic levels in surface water and sediment are 218 microplastic/m3 and 1159 microplastic/kg dry weight, respectively. The fiber is the most shape of microplastics in all samples. The colors of microplastics was evaluated, there are 6 colors: white, green, blue, black, gray and red with the white is the most popular. This research provides a database on microplastic pollution in surface water and sediment in the Tien River basin.