Water Quality Sampling Research Articles

DAMPAK PENGELOLAAN SAMPAH PADAT TERHADAP KUALITAS AIR PANTAI BATAKAN, TANAH LAUT KALIMANTAN SELATAN

Batakan Village, Panyipatan District, Tanah Laut Regency is one of the villages in South Kalimantan, which in addition to having natural tourism potential is also a fishing village. This study aims to analyze the impact of solid waste management on batakan beach water quality. Sampling at the location is taken by means of instantaneous sampling (grab sample). A misguided sample or grab sample is a sample taken directly from a body of water that is on the beach. The water quality sampling procedure uses the surface water sampling method in accordance with SNI 6989.57:2008, at the sampling point locations that have been determined purposively. Research parameters in the form of physics, namely temperature and brightness. Chemistry in the form of pH, Do, salinity, TSS, COD and BOD. Based on the results of water quality measurements obtained several parameters that meet the water quality standards for marine biota, namely the research parameters in the form of physics, namely temperature and brightness. Chemistry in the form of pH, DO, salinity, COD and BOD. Meanwhile, TSS does not meet the standards of the Decree of the State Minister of the Environment No. 51 in 2004.

KAJIAN STATUS MUTU AIR, INVENTARISASI SUMBER PENCEMAR DAN ALTERNATIF STRATEGI PENGENDALIAN PENCEMARAN SUNGAI BARABAI KABUPATEN HULU SUNGAI TENGAH

Barabai River is one of the rivers in Hulu Sungai Tengah District which is widely used by the surrounding community for household, agricultural and industrial activities. Community activities around the Barabai River certainly have an impact on the decline in river water quality because the waste produced generally goes directly to other environments without prior processing. This study aims to analyze the water quality status of the Barabai River, take an inventory of the potential sources of water pollution in the Barabai River and formulate alternative strategies for controlling water pollution in the Barabai River. The research was located on the Barabai River along ± 43.2 km which started from Tanjung Village, Hantakan District, towards Jaranih Village, Pandawan Subdistrict, to Tabat Village, Labuan Amas Utara Subdistrict. The water quality status of the Barabai River was calculated using secondary data from the 2017-2020 river water quality monitoring results sourced from the Department of Environment and Transportation of Hulu Sungai Tengah District using the pollutant index method. Potential sources of pollutants in the Barabai River were inventoried based on domestic, industrial and agricultural activities around the monitoring point for water quality sampling by collecting secondary data and field survey results, then a map of the distribution of each water pollutant source was described using the Geographic Information System (GIS) application. Alternative policy strategies for controlling pollution of the Barabai River were analyzed using the SWOT method based on the Regulation of the State Minister of the Environment Number 01 of 2010 concerning the management of water pollution control. The results showed that in 2018 the water quality status of the Barabai River met the quality standards while in 2017, 2019 and 2020 the status of the water quality was lightly polluted with parameters that did not meet the quality standards, namely Total suspended solid (TSS), Dissolved Oxygen (DO), Biological Oxygen Demand (BOD) and Fecal Coli. Potential sources of pollutants in the Barabai River consisted of domestic pollutant sources originating from residential activities in the Barabai River area, potential sources of Pollution Point Source (Institutions) originating from ± 21 types of businesses /activities located in Hulu Sungai Tengah District and potential sources of Non-Point pollutants Source coming from agricultural activities of rice fields and plantation. Alternative policy strategies for controlling the pollution of the Barabai River can be done by adding water quality monitoring points in industrial areas, improving river water quality, raising public awareness of waste management through sustainable and targeted socialization, tightening supervision of compliance with business people, expanding coordination inter-agency, controlling waste entering rivers, determining the capacity of water pollutant loads, constructing a wastewater treatment plants (IPAL), carry out an inventory and identification of water pollutant sources based on the Regulation of the Minister of the Environment Number 01 of 2010, and stipulate a Regional Regulation on licensing for the disposal of wastewater to water sources.

Impacts of Regulated Water Service Extension on Water Quality, Perception, and Affordability in Orleans, NY

There are increasing advocacy and policy efforts to consolidate private wells and other small systems into larger regulated systems to address water quality-related public health and climate resilience challenges. However, little is known about how trade-offs between water quality and affordability implications of these consolidation efforts are experienced and perceived by residents. Here, we analyzed changes in water quality, affordability, and perception associated with a groundwater contamination-motivated transition from private well to regulated municipal water. We conducted water quality samplings and household surveys pre- and post-municipal service extension in the Town of Orleans, NY. Our findings illustrate that water quality improved due the connection to municipal service, resulting in increased consumption of tap water, improved perception of water quality and reliability, and decreased use of household treatment, but with a much higher monthly expenditure. Residents reported general satisfaction with their new municipal water service; however, the cost of service was more than expected, and some were dissatisfied with the taste of chlorine in the municipal supply. Despite the positive public health implications, it is important to consider the trade-offs in regulated water transitions and the perceptions of residents to foster successful, sustainable solutions.

Using multispectral drones to predict water quality in a subtropical estuary

ABSTRACT Drones are revolutionising earth system observations, and are increasingly used for high resolution monitoring of water quality. The objective of this research was to test whether drone-based multispectral imagery could predict important water quality parameters in an ICOLL (intermittently closed and opened lake or lagoon). Three water quality sampling campaigns were undertaken, measuring temperature, salinity, pH, dissolved oxygen (DO), chlorophyll (CHL), turbidity, total suspended sediments (TSS), coloured dissolved organic matter (CDOM), green algae, crytophyta, diatoms, bluegreen algae and total algal concentrations. DistilM statistical analyses were conducted to reveal the bands accounting for the most variation across all water quality data, then linear correlations between specific band/band ratios and individual water quality parameters were performed. DistilM analyses revealed the NIR band accounted for most variation in March, the Green band in April and the RE band in May, and showed that the most important contributors varied significantly among campaigns and variables. Significant linear correlations with R 2 > 0.4 were obtained for eleven of the water quality parameters tested, with the strongest correlation obtained for CHL and the green band (R 2 = 0.72). The relative importance of predictor bands and observed water quality parameters varied temporally. We conclude that drones with a multispectral sensor can produce useful ‘snapshot’ prediction maps for a range of water quality parameters, such as chlorophyll, bluegreen algae and dissolved oxygen. However, a single model was insufficient to reproduce the temporal variation of water parameters in dynamic estuarine systems.

Water quality negatively impacts coral occurrence in eutrophic nearshore environments of the Florida Keys

IntroductionCoral species are negatively impacted by anthropogenic stressors worldwide. Nearshore coastal ecosystems provide an excellent study system for the investigation of the impacts of local land-based stressors such as nutrients on coral assemblages due to their proximity to land based sources of pollution. The nearshore environs of the Florida Keys are an intensively developed and intensively managed system; Florida Keys waters have been characterized by chronic eutrophication since 1999. Benthic communities are known to change or “shift” under chronic eutrophication.ObjectivesThis research examines the patterns of occurrence in stony corals correlating to detailed nearshore water quality measurements. The questions addressed are a) What are the coral assemblages within 500 meters of the shoreline, and which species are resilient to these environs? b) How does water quality impact coral occurrence?MethodsThis study examined the immediate nearshore (0-500m) areas of 13 sites using a randomized blocked experimental design for both water quality and benthic sampling. Water quality parameters measured included chlorophyll-a, nitrates + nitrites (NOx), total nitrogen, total Kjeldahl nitrogen, total phosphorus, Salinity, pH, temperature, and dissolved oxygen. Benthic surveys documented stony coral occurrence using belt transects with point intercept measurements.ResultsStony coral species occurrence was limited at most of the study sites. Siderastrea radians and Porites divaricata were the two common species that appear to have a higher tolerance to eutrophic conditions under these shallow water conditions. Of the 13 study sites, 2 sites had no coral species occurring; this analysis was based on the comparison between sites with and without stony coral species. Water column Chlorophyll-a, pH, dissolved oxygen saturation, temperature, NOx, N:P ratio, total nitrogen and total phosphorus were found to be significantly different between the sites with and without corals. Further multivariate analysis showed a clear clustering of the two groups.ConclusionThe low overall diversity and the higher occurrences of stress tolerant species provide evidence of the effects of coastal eutrophication on the coastal Florida Keys ecosystem. Our data suggest that more conservative water quality thresholds should be posed to improve nearshore biodiversity and ecological functioning of coastal systems.

Land Used Mapping using Unmanned Aerial Vehicle (UAV) along Parit Rasipan Drainage System

Excess nutrients accelerate the growth of plants and algae in water sources, leading to environmental issues like flow retardation (flood), a decrease in the amount of oxygen in the water, and a decline in the quality of the water. Therefore, the goal of this study is to identify the qualityParit Rasipan drainage system's eutrophic level in terms of temperature, dissolved oxygen, pH, and turbidity; and to analyse an NDVI (Normalized Difference Vegetation Index) image taken by unmanned aerial vehicle (UAV) and using Agisoft photoscan software. As a result, four sampling locations—residential (S1), industrial (S2), agricultural (S3), and farming (S4)—have been chosen for water quality sampling and analysis along the Parit Rasipan drainage system. The HACH method wasused to analyse water samples that have been obtained according to the Standard Methods for Water and Wastewater Examinations. It was found that agricultural zone waspoor water quality compared residential, industrial and farmingzoneswithmeasurements of 3.82 mg/L, 3.09, 25.57 °C, and 14.6 NTU, respectively, the agricultural zone hasthe highest values for thefour metrics of dissolved oxygen, pH, temperature, and turbidity. This scenario could be due to the usage of the fertilizerto cultivate the oil palmcontributed toParit rasipan drainage system (S3)which resulted in asubstantial amount of eutrophication. Hence, the use of UAVs and the agisoft photoscan programme has considerably improved the mapping of the water quality metrics and eutrophic level.

Evaluation of statistical models: Perspective of water quality load estimation

The accurate representation of the load of water quality constituents, transported by rivers and streams, is crucial to understand the impact on the quality of the lakes, the behavior of the rivers and streams. Statistical models have been developed to predict the water-quality constituent loads from the available data of sampled concentration (low-frequency/grab chemistry data) and continuous discharge (high frequency) at a particular sampled location and to further analyze trends and changes in water quality. However, the performance of statistical models to estimate water quality constituent loads depends on many aspects including the type of water quality constituent, sampling strategy and frequency, and the land use and areas of the watershed. This study evaluates the performance of a wide range of statistical models for the estimation of total suspended solids (TSS) and total phosphorus (TP) loads under various sampling scenarios and monitoring stations in Southern Ontario, Canada. Trends in TSS and TP concentrations and loads were further analyzed in major tributaries. The Weighted Regression on Time, Discharge, and Season Kalman Filter (WRTDS_K) model was found to be the most suitable model (p > 0.05 and Percentage Difference (%) (PDIFF) between ±20) for predicting TSS loads at most sampling stations and under most sampling scenarios, while, the Weighted Regression on Time, Discharge, and Season (WRTDS) model was found to be the most suitable model (p > 0.05 and flux bias statistics (FBS) between ±0.1) for predicting TP loads. The applied statistical models (LOADEST simple and curvilinear models, WRTDS, WRTDS_k, Beale’s estimator, composite and interpolation models) have shown a limited potential to estimate load accurately at monitoring stations covering small drainage areas.

Dissolved Heavy Metal Pollution and Assessment of a Karst Basin around a Mine, Southwest China.

Karst water quality is one of the most important environmental issues in karst areas. The study's purpose was to investigate dissolved heavy metal pollution and health risk assessment in karst water basins around mines. River water and groundwater samples were analyzed by principal component analysis, correlation analysis, water quality index, hazard quotient, and hazard index. Median concentrations of dissolved heavy metals in the Sidi River were similar to the world average with a slightly alkaline characteristic. The concentrations of most dissolved heavy metals in river water were higher than those in groundwater. The concentrations of Zn, Pb, and Cd around the mine exceeded the limits of drinking water indicators. The poor water quality samples with high water quality index values were distributed around the mine. Lead (Pb), Zn, As, Cd, and Cr were potentially threatening metals in the study area. The pollution level of dissolved heavy metals in the Sidi River was at a medium level compared with other rivers worldwide. Principal component analysis and correlation analysis showed that Cu, Pb, Zn, Cd, Mn, Fe, As, and Sr mainly came from mine drainage; Ca2+, Mg2+, and Cr mainly came from the contribution of carbonate rocks; Na+ and K+ were related to local human agricultural activities. The concentrations of dissolved heavy metals in groundwater were affected by karst aquifers. The results of this study can provide a data reference for water resources prevention and human health protection in the Sidi River's karst basin and similar karst basins.

Satellite and Machine Learning Monitoring of Optically Inactive Water Quality Variability in a Tropical River

Large-scale monitoring of water quality parameters (WQPs) is one of the most critical issues for protecting and managing water resources. However, monitoring optically inactive WQPs, such as total nitrogen (TN), ammoniacal nitrogen (AN), and total phosphorus (TP) in inland waters, is still challenging. This study constructed retrieval models to explore the spatiotemporal evolution of TN, AN, and TP by Landsat 8 images, water quality sampling, and five machine learning algorithms (support vector regression, SVR; random forest regression, RFR; artificial neural networks, ANN; regression tree, RT; and gradient boosting machine, GBM) in the Nandu River downstream (NRD), a tropical river in China. The results indicated that these models can effectively monitor TN, AN, and TP concentrations at in situ sites. In particular, TN by RFR as well as AN and TP by ANN had better accuracy, in which the R2 value ranged between 0.44 and 0.67, and the RMSE was 0.03–0.33 mg/L in the testing dataset. The spatial distribution of TN, AN, and TP was seasonal in NRD from 2013–2022. TN and AN should be paid more attention to in normal wet seasons of urban and agricultural zones, respectively. TP, however, should be focus on in the normal season of agricultural zones. Temporally, AN decreased significantly in the normal and wet seasons while the others showed little change. These results could provide a large-scale spatial overview of the water quality, find the sensitive areas and periods of water pollution, and assist in identifying and controlling the non-point source pollution in the NRD. This study demonstrated that multispectral remote sensing and machine learning algorithms have great potential for monitoring optically inactive WQPs in tropical large-scale inland rivers.

Wetland Functional Area Division Method: A Correlation Analysis of Water Quality and Landscape Structure

The purpose of this study is to provide a clearer idea for the optimization of wetland functional areas and a new method for the identification and analysis of wetland functional areas under the background of the latest Wetland Protection Law in China. This study selected Pan’an Lake Wetland, the first national wetland park built in coal mining subsidence land in China, as the research object. By constructing a “Water-water-landscape-function” (WLF) model, combined with landscape pattern index and Nemerov pollution index method (NPI), the differences in water quality and landscape structure of different functional areas were analyzed. Then, Pearson’s Correlation Analysis and Redundancy Analysis are combined to quantitatively analyze the correlation between water quality environment and landscape structure. Finally, Inverse Distance Weighting (IDW) was introduced to help study the spatial difference in water quality in different functional areas. This study lasted for one year. Twelve water quality sampling points were set up, and 216 effective samples were collected monthly for one year. The results showed that: (1) the ratio of built-up land and cultivated land area had a high impact on water quality indicators in each water period, especially the increase in cultivated land patch density would increase the risk of TN and TP losing to surrounding water bodies; (2) the lakes and rivers in the wetland park have good ecological effects and should be widely used in various functional areas; (3) the degree of landscape fragmentation was negatively correlated with the overall water quality, while the degree of landscape agglomeration and landscape diversity were positively correlated with the overall water quality; (4) ecological corridors should be established between WCA and WRA, artificial corridors should be established between MEA and LEA, and ecological interception should be set between MEA and WRA; and (5) the “Water-quality-landscape-function” (WLF) model is an effective tool for the analysis and optimization of wetland functional areas, which provides a reference for the new round of wetland planning in China.

Transcriptional Responses of Stress-Related Genes in Pale Chub (Zacco platypus) Inhabiting Different Aquatic Environments: Application for Biomonitoring Aquatic Ecosystems.

Pale chub (Zacco platypus) is a dominant species in urban rivers and reservoirs, and it is used as an indicator to monitor the effects of environmental contaminants. Gene responses at the molecular level can reflect the health of fish challenged with environmental stressors. The objective of this study was to identify correlations between water quality factors and the expression of stress-related genes in Z. platypus from different lake environments (Singal and Juam Lakes). To do so, transcriptional responses of genes involving cellular homeostasis (heat-shock protein 70, HSP70; heat-shock protein 90, HSP90), metal detoxification (metallothionein, MT), and antioxidation (superoxide dismutase, SOD; catalase, CAT) were analyzed in the gill and liver tissues of Z. platypus. HSP70, HSP90, and MT genes were overall upregulated in Z. platypus from Singal Lake, which suffered from poorer water quality than Juam Lake. In addition, gene responses were significantly higher in Singal Lake outflow. Upregulation of HSP70, HSP90, and MT was significantly higher in Z. platypus gills than in the liver tissue. In addition, integrated biomarker response and heatmap analysis determined correlations between expression of biomarker genes or water quality factors and sampling sites of both lakes. These results suggest that stress-related genes used as multiple biomarkers may reflect spatial characteristics and water quality of different lake environments, and they can be used for biomonitoring and ecological risk assessment.

Prevalence Analysis of Hypodermal Infectious and Haematopoetic Necrosis Virus (IHHNV) in Vaname Shrimp (Litopenaeus vannamei) in Bengkalis District

The disease is a limiting factor and causes economic losses in the cultivation of white shrimp (Litopenaeus vannamei). Diseases in vaname shrimp are caused by viruses, microbes, parasites, organisms, and natural conditions. One of these diseases is infectious hypodermal and hematopoietic necrosis (IHHNV). This study was conducted from February to April 2022. This study aimed to analyze the prevalence of IHHNV that attacks white shrimp in the Bengkalis Regency and to observe and observe clinical symptoms in whitewashed shrimp infected with IHHNV in the pond area of the Bengkalis Regency. The research method used in this study is a survey method. The primary data taken included water quality observations, morphological observations, sampling, and detection of IHHNV using the polymerase chain reaction (PCR) method. The results showed that the prevalence of IHHNV in white shrimp was 0%. PCR testing using a specific primer measuring 392bp showed that white shrimp samples from three locations in Bengkalis District, namely Bengkalis District, Bukit Batu District, and Rupat District, were negative for IHHNV and did not show any clinical symptoms of IHHNV on morphological examination

A device to collect passive, flow‐weighted water samples from surface runoff

Obtaining water quality samples from surface runoff is essential for understanding erosion and pollutant transport processes. Existing water sampling devices are expensive, require installation of extensive infrastructure or power supplies, or have limited ability to collect flow-weighted samples. We created an inexpensive, nonpowered, flow-weighted water sampling device that can be incorporated into runoff quantification systems like the Upwelling Bernoulli Tube (UBeTube). Our device, called the Holey Sampler, consists of a standpipe with holes drilled at specific heights. Water enters the standpipe in proportion to the water flow rate through the UBeTube and is routed to an external collection bottle. We built and tested two versions of the Holey Sampler that sampled water at an approximate ratio of 1:250 of the runoff rate. The Standard Opening Holey Sampler (Standard-OHS) configuration was made with 1.6-mm-diam. holes, whereas the Miniature Opening Holey Sampler (Mini-OHS) configuration was designed to prevent oversampling at low outflows but required drill bit of smaller diameter (0.8-mm). Laboratory and numerical experiments demonstrated that both configurations obtained accurate flow-weighted runoff samples when incorporated into the UBeTube. Flow rates in the Mini-OHS were better correlated with runoff rates under constant-flow (R2 = .992 vs. .965 for the Standard-OHS) and variable-flow conditions (R2 = .996 vs. .954 for the Standard-OHS). Further modification of the Holey Sampler could also allow flow-weighted sampling of other runoff quantification devices like flumes and weirs.

Source water vulnerability to elevated total dissolved solids within a mixed-use Appalachian River basin

The upper Monongahela River basin in West Virginia represents a watershed wherein historic land use activities, including coal mining, conventional oil and gas development, and residential and urban development have contributed to elevated total dissolved solids (TDS) concentrations within surface and source waters with widespread exceedance of the 500 mg/L secondary drinking water standard for TDS. Our research was designed to characterize spatial variability in and sources of elevated and assess vulnerability of surface and source waters to additional TDS sources and loading. We compiled 3439 unique water quality sampling records throughout the study area over a ten-year period and applied boosted regression tree (BRT) analysis to model log[x]-transformed TDS as a function of landscape attributes across the 885 sampled NHD catchments. We predicted (i.e., elevated TDS and reduced dilution capacity) and observed (i.e., increased variability in TDS and temporary exceedances of 500 mg/L) elevated vulnerability of source waters, with vulnerability being largely driven by a few dominant contributors of TDS throughout the stream network. Notably, seven 12-digit hydrologic unit code (HUC) inflows to the Monongahela River and its vulnerable tributaries were predicted to require a combined 6,664,879 m3 of water (i.e., chemical footprint) to dilute TDS concentrations below 500 mg/L from July through September. Our results provide insights into how the mixed land uses containing extractive industries can impact water quality and demonstrates the importance of both spatial and temporal processes in controlling vulnerability of source waters to water pollution.

Multifactor prediction of sea water quality based on improved K-LSTM

To solve the problem of multifactor sea water quality accurate prediction, a prediction model based on the integration of the improved k-means clustering algorithm and Long-short term memory (K-LSTM) was proposed. Firstly, the random forest method is used to fill the missing values for each factor in the dataset. Then, the improved k-means algorithm is used to denoise the water quality samples according to the multifactor time series of water quality. Finally, an LSTM neural network is used to establish the multifactor prediction model of water quality. In this study, the water quality data of five typical sampling points in Niuguwan Ecological breeding Bases from 2017 to 2021 were selected for training and testing. The RMSE of the model was reduced by 23%, and the MAE was reduced by 60%. The results showed that the water quality indexes of the five monitoring stations were improved, but the PH value showed a rising trend, the water quality was alkaline, and the total phosphorus content exceeded the standard. This model has completed the accurate prediction of sea water quality in Niuguwan ecological breeding bases, which provides a new idea for water environment protection.

Evaluation of hydrochemistry and identification of pollution hotspots of little Akaki river using integrated water quality index and GIS

Despite unwavering effort of the government, urban river pollution in Ethiopia has remained a worrisome phenomenon now a days. This research is conducted with a prime aim of assessing and evaluating the water quality status and identifying and mapping of the pollution hotspots in the Little Akaki River (LAR), Ethiopia by integrating the water quality index (CCME-WQI) and Geographic Information System (GIS). Accordingly, water quality samples were collected from 22 monitoring stations. The water samples were collected and analyzed for physico-chemical and heavy metal constituents using the American Public Health Association (APHA) standard methods. Most of the physico-chemical constituents analyzed have surpassed the standard guideline value of the country and World Health Organization (WHO). In addition, most of the middle (S3-S10) segments of the river is heavily polluted than the downstream segment (S11-S14) and upstream segments. Similarly, the heavy metals concentrations in the LAR have decreasing trend with Mn>Zn>Pb>Cu>Cd. On the other hand, the overall CCME-WQI modeling output ranged from 18.9 – 36.2. Accordingly, the finding of the study reveals that most water quality parameters were beyond ambient surface water quality standards and the CCME-WQI categorizes all the monitoring stations under poor water quality state. Besides, the spatial distribution of pollution in LAR shows intense deterioration at the middle segment of the river and needs a proper strategic management plan in the catchment and immediate protection and restoration of the natural ecology of the LAR. It is recommended to integrate river water pollution management and maintain ecologically to achieve healthy urban development.

A field study of near-junction-apex flow at a large river confluence and its response to the effects of floodplain flow

• A field survey on flow at a large confluence of a compound tributary was conducted. • Kinetic energy and momentum correction coefficients at confluence were identified. • Floodplain flow decreased the size of stagnation zone and impacted its location. • Floodplain flow shifted the location of the mixing interface towards the centerline. • Floodplain flow was found to impact on the characteristics of the secondary flow. A field investigation was carried out in March 2019 at the large river confluence between the Yangtze River and the outflow channel with a large inner-side floodplain of Poyang Lake using acoustic Doppler current profiling (ADCP) and water quality sampling. The study was intended to complement previous field studies carried out under different flow conditions in August and December 2018 and to investigate the effects of the alternate flow mechanism (compound channel vs single channel) of the Poyang Lake outflow channel on confluence dynamics. The main hydrodynamics and morphodynamics features were identified and comparatively discussed with those from the previous field studies. The kinetic energy and momentum correction coefficients were found to peak near the confluence apex and decay farther downstream reflecting the gradual flow recovering process in the post-confluence channel. The alternate flow mechanism (compound channel vs single channel) of the Poyang Lake outflow channel and the change in momentum flux ratio M R were found to significantly impact on the characteristics of the stagnation zone, mixing interface and secondary flow at the confluence. The smallest and the largest stagnation zone were observed at the lowest M R and as the outflow channel acted as single channel, respectively, while also the location of the mixing interface was impacted. Furthermore, secondary flow consisting of dual counter-rotating helical cells and channel scale circulation were observed as the Poyang Lake outflow channel acted as compound channel and a single channel, respectively. These results provide novel information about confluence dynamics in large river systems where one tributary may have a floodplain flow in flooding conditions.

Combining the multivariate statistics and dual stable isotopes methods for nitrogen source identification in coastal rivers of Hangzhou Bay, China.

Coastal rivers contributed the majority of anthropogenic nitrogen (N) loads to coastal waters, often resulting in eutrophication and hypoxia zones. Accurate N source identification is critical for optimizing coastal river N pollution control strategies. Based on a 2-year seasonal record of dual stable isotopes ({updelta}^{15}mathrm{N}-{mathrm{NO}}_3^{hbox{-} } and {updelta}^{18}mathrm{O}-{mathrm{NO}}_3^{hbox{-} }) and water quality parameters, this study combined the dual stable isotope-based MixSIAR model and the absolute principal component score-multiple linear regression (APCS-MLR) model to elucidate N dynamics and sources in two coastal rivers of Hangzhou Bay. Water quality/trophic level indices indicated light-to-moderate eutrophication status for the studied rivers. Spatio-temporal variability of water quality was associated with seasonal agricultural, aquaculture, and domestic activities, as well as the seasonal precipitation pattern. The APCS-MLR model identified soil + domestic wastewater (69.5%) and aquaculture tailwater (22.2%) as the major nitrogen pollution sources. The dual stable isotope-based MixSIAR model identified soil N, aquaculture tailwater, domestic wastewater, and atmospheric deposition N contributions of 35.3 ±21.1%, 29.7 ±17.2%, 27.9 ±14.5%, and 7.2 ±11.4% to riverine {mathrm{NO}}_3^{hbox{-} } in the Cao’e River (CER) and 34.4 ±21.3%, 29.5 ±17.2%, 27.4 ±14.7%, and 8.7 ±12.8% in the Jiantang River (JTR), respectively. The APCS-MLR model and the dual stable isotope-based MixSIAR model showed consistent results for riverine N source identification. Combining these two methods for riverine N source identifications effectively distinguished the mix-source components from the APCS-MLR method and alleviated the high cost of stable isotope analysis, thereby providing reliable N source apportionment results with low requirements for water quality sampling and isotope analysis costs. This study highlights the importance of soil N management and aquaculture tailwater treatment in coastal river N pollution control.

Evaluation of sampling frequency impact on the accuracy of water quality status as determined considering different water quality monitoring objectives

Water quality sampling is a key element in tracking water quality monitoring objectives. However, frequencies adapted by different agencies might not be sufficient to provide an accurate indication of water quality status. In this study, data from low- and high-resolution water quality datasets were analyzed to determine the extent to which monitoring objectives could be achieved with different sampling frequencies, with a view to providing recommendations and best practices for water quality monitoring frequency in places with limited resources with which to implement a high-frequency monitoring plan. Water quality data from two watersheds (Maumee River and Raisin River) located in the Western Lake Erie Basin (WLEB) were used since these watersheds have consistent records over substantial periods of time, and the water quality data available have a high resolution (at least daily). The water quality constituents analyzed included suspended solids (SS), total phosphorus (TP), soluble reactive phosphorus (SRP), and nitrate + nitrite (NO2+3). Sources of pollutants for watersheds located in the WLEB include contributions from point sources like discharges from sewage treatment plants and non-point sources such as agricultural and urban storm runoff. Weekly, bi-weekly, monthly, and seasonal datasets were created from the original datasets, following different sampling rules based on the day of the week, week of the month, and month of the year. The resulting datasets were then compared to the original dataset to determine how the sampling frequency would affect the results obtained in a water quality assessment when different monitoring objectives are considered. Results indicated that constituents easily transported by water (such as sediments and nutrients) require more than 50 samples/year to provide a small error (< 10%) with a confidence interval of 95%. Monthly and seasonal sampling were found appropriate to report a stream's prevailing water quality status and statistical properties. However, these resolutions might not be sufficient to capture long-term trends, in which case bi-weekly samples would be preferable. Limitations of low-resolution sampling frequency could be overcome by including rainfall events and random sampling during specific time windows as part of the monitoring plan.

Microbiological contamination of drinking water sources in tourist accommodations in South Luangwa National Park, Zambia

Background: Water quality for tourists visiting South Luangwa National Park and other less developed regions is of the utmost importance in order to avoid gastrointestinal infections; one of the most common diseases among tourists. It is also important to the health of the local tourist accommodations and the local tourist economy.Methods: Water quality samples assessing microbiological contamination were taken from the borehole and point of use in 14 tourist lodges and camps. Turbidity was assessed optically with a DelAlgua turbidity tube. For microbiological analysis, samples were incubated in the DelAgua Dual Incubator at 37°C and 44°C. Thermotolerant Escherichia coli (E. coli) was used as theindicator bacterium for fecal pollution. Water samples were classified based of risk levels for pollution determined by the World Health Organization (WHO)Results: Fifty percent of borehole samples showed no contamination. Two were found to be at high risk and the others ranged between low and intermediate risk. At the point of use, 80% of the samples were clean and compliant with WHO guidelines. Water contamination generally improved from the borehole to point of use. Turbidity at borehole samples were clear in 75% ofpossible samples. At the point of use, turbidity was clear in 81% of samples.Conclusion: This study establishes the first baseline water quality data for tourist facilities at South Luangwa National Park in Zambia. While water quality at most sites is clean for human use, a regular monitoring system accompanied by maintenance is recommended.