Measured Water Quality Parameters Research Articles

Advancing reservoirs water quality parameters estimation using Sentinel-2 and Landsat-8 satellite data with machine learning approaches

Reservoir eutrophication, caused by human activities and climate change, has emerged as a critical environmental concern that has attracted both governmental and public attention. However, accurate measurement of water quality parameters, such as chlorophyll a (CHL-a), water clarity (Secchi depth; SD), and total suspended solids (TSS), in inland waters is challenging due to the optical complexity of individual water bodies, which impedes the optimization of conventional bio-optical algorithms. The aim of this study was to demonstrate the viability of harmonizing Sentinel-2 Multi-Spectral Imager (MSI) and Landsat-8 Operational Land Imager (OLI) satellite imagery surface reflectance (SR) products to facilitate the monitoring of inland reservoir CHL-a, SD, and TSS using the Google Earth Engine (GEE) platform and machine learning algorithms. Machine learning models were trained using Landsat-8 OLI and Sentinel-2 MSI surface reflectance products to identify bands and combinations predicting CHL-a, SD, and TSS. Among the machine learning algorithms tested, random forest (RF) (S-2 MSI: R2 = 0.61, mean absolute error [MAE] = 6.56%, root-mean-square error [RMSE] = 12.51 μg/L, L-8 OLI: R2 = 0.56, MAE = 8.44%, RMSE = 16.01 μg/L) yielded the best results in the test set for CHL-a prediction from the Sentinel-2 MSI and Landsat-8 OLI, outperforming the k-nearest neighbor (KNN), AdaBoost, and artificial neural network (ANN) models. It also showed superior performance for SD and TSS prediction. The feature importance analysis revealed that specific band ratios, such as (red/red edge1)*red edge2 for Sentinel-2 MSI and red/blue for Landsat-8 OLI, were significant predictors of CHL-a and TSS. The red/blue band ratio and the green band were highly predictive for SD in Sentinel-2 MSI and Landsat-8 OLI, respectively. The results of fall CHL-a predictions revealed varying trophic levels in the reservoirs. Landsat-8 OLI indicated that 2% of the reservoirs were oligotrophic, while 46%, 43%, and 9% were mesotrophic, eutrophic, and hypertrophic, respectively. Meanwhile, the Sentinel-2 MSI results showed that 51% of the reservoirs were mesotrophic, while 6%, 35%, and 8% were oligotrophic, eutrophic, and hypertrophic, respectively. Overall, this study demonstrates the effectiveness of Landsat-8 OLI and Sentinel-2 MSI surface reflectance products in estimating and monitoring reservoir water quality parameters using machine learning algorithms. This approach has the potential to yield valuable insights aiding the assessment and management of water quality at the regional, national, and global levels.

GASTROPOD DIVERSITY AS A BIO-INDICATOR OF AQUATIC POLLUTION IN SIRONJONG GADANG ISLAND PESISIR SELATAN DISTRICT

This study aims to determine the diversity of gastropods and water conditions on Sironjong Gadang Island, Pesisir Selatan Regency. This research was conducted in August 2022 in the waters of Sironjong Gadang Island and the Marine Biology Laboratory and Marine Chemistry Laboratory of the Department of Marine Science, Universitas Riau. The method used in this research is the survey method, which is direct observation of the research area and sampling and measurement of water quality parameters in the field. The results of the study found gastropod species consisting of 4 (four) families, 4 (four) genera, and 8 (eight) species. The diversity value (H') was at a moderate level of diversity. The highest gastropod density was found at Station I, with a density value of 16.33 ind/m², and the lowest density was found at Station III, with a density value of 13.89 ind/m². The highest relative density was Monodonta labia species, with a relative density value of 27.6%, while the lowest relative density was Haustrum-scoring species, with a relative density value of 3.3%. Temperature 28-29˚C; salinity 25-27 ppt; pH 7.91-7.95; brightness 1.55-2.65 m. The sediment type at Station I was dominated by muddy gravel, Station II was dominated by sandy gravel, and Station III was defeated by sandy gravel with a total sediment organic matter content of 6.10-10.05%.

Fish Growth Performance in RAS Pond Using Hydrocyclone Mechanical Filter

The high feeding and the metabolic output of the fish in intensive aquaculture can cause various problem, such as poor water quality and slowing down the fish growth performance. Recirculating Aquaculture System (RAS) is a solution to maintain water quality. Unfortunately, the conventional mechanical filter in RAS such as japmat is inefficient. One strategy that can be applied is to use a hydrocyclone. This research aims to observe the fish growth performance in RAS pond using hydrocyclone mechanical filter and its comparison with the use of japmat. Research method was performed by comparing hydrocyclone and japmat in the pond with the RAS system. The research design is completely randomized design (CRD), with three replications in each treatment. The research was carried out through five stages, namely hydrocyclone set-up, RAS ponds set-up, water quality analysis, fish growth measurement, and statistical analysis. Based on the Independent Samples Test, the use of hydrocyclone mechanical filters has a significant effect (P<0.05) on the measured water quality parameters (DO, Temperature, pH, TDS, NH3) except for NO2. Hydrocyclone significantly affect Average Daily Growth and Specific Daily Growth parameters. Whilst, the Survival Rate and Feed Conversion Ratio parameters, it did not give significant effect

Water Quality and Dissolved Organic Carbon Content in Agricultural Streams: Northern Nile Delta Region, Egypt

Sustainable development goals (SDGs) 2 (zero hunger), 6 (clean water and sanitation), and 15 (life on land) are related to the human-water-soil nexus. Soil organic carbon and nutrients can be removed and transported to waterways through runoff and drainage. The main goals of this study are to quantify the water quality for irrigation and assess the dissolved organic carbon (DOC) contents in streams in the northern Nile Delta, Egypt. A 4-year water quality monitoring program is accomplished by collecting 35 irrigation and drainage water samples per year from the study area. The measured water quality parameters are as follows: salinity, pH, Na, SAR, Cl, and NO3–N. In addition, the DOC content is accessed. The salinity hazard ranged from moderate, for most irrigation samples, to high and very high for drainage samples. All collected water samples have low to medium sodium hazards. Results indicate that average DOC contents in irrigation canals are 2.32 and 2.93 mg L−1 for the summer and winter, respectively. The respective means of DOC concentration in drainage canals for the summer and winter seasons are around 3.96 and 5.09 mg L−1. This study revealed significant differences in EC, pH, Na, Cl, and SAR, as water quality parameters, between irrigation and drainage canals. Additionally, the studied agroecosystem has seasonal variability in DOC concentration in irrigation and drainage canals between summer and winter. Overall, reusing drainage water for irrigation in the study area requires the selection of suitable crops and site-specific management.

The Effect of Providing Different Natural Feeds on The Growth of Manfish (Pterophyllum scale)

Decorative fish is a significant fishery product since it tends to be finished by exporters, one of the elaborate fish that adjusts to be sent out is manfish on the grounds that it has the excellence of variety and agile developments. The growth of manfish can be influenced by appropriate feed, so this study aims to find out what type of natural feed is suitable for the growth of manfish with artificial feed comparisons (pellets). The treatments used in this study were 100% artificial feed (petet) as control/P0, 100% Daphnia sp as 1/P1 treatment, 100% Tubifex as 2/P2 treatment, and 50% Daphnia sp and 50% Tubifex as 3/P3 treatment. The parameters observed during the study were absolute weight growth, absolute length growth, survival rate, water quality, and feed conversion ratio. The results showed a treatment that used good natural feed in the long growth of manfish, namely P1 treatment of 100% Daphnia sp feed by showing a figure of 5.27±0.29 cm. The absolute weight growth parameters in good natural feed treatment are P1 treatment of 100% Daphnia sp with a figure of 3.20±0.34 g. The results of the study with feed conversion ratio parameters in natural feed treatment showed the results that P1 treatment experienced high fish appetite because feed needs during the study showed a figure of 11454.02 mg. The lowest survival rate was obtained in the control at 66.67% and the highest survival rate at P1 treatment at 91.67%. The measured water quality parameters are temperature, pH, salinity, and dissolved oxygen which each show numbers in the range of 27-17oC, 00/00, 7-8 and 4-5mg/L.

Ecophenotypic Variation of Midas Cichlid, Amphilophus citrinellus (Gunther, 1864), in Lake Batur, Bali, Indonesia.

Cichlid fishes exhibit rapid adaptive radiations with significant diversification rates in response to ecological variability, i.e., ecological opportunity or geographical isolation. The discovery of a Midas cichlid species in Lake Batur, Indonesia's largest volcanic lake, first reported in 2013, could represent such adaptations. Midas cichlids can now be found in a range of habitats in Lake Batur and dominate the lake's fish population by up to 60%. This study aimed to identify the interaction between habitat, water quality, and Midas cichlid in Lake Batur, facilitating morphometric variances in the fish populations. The fish were captured at five locations in Lake Batur using fishing rods, community nets with mesh sizes of 2-3 inches, experimental gillnets with mesh sizes of 1 inch, and fish scoops in floating net cages during August and November 2022. There were 46 fish samples caught from the five stations, all photographed using a digital camera and later measured using the ZEN 2012 software. The fish measurement employed a truss morphometric method using 21 distinct morphometric body features. Canonical analysis was used to determine the distribution of characteristics, while discriminant analysis was used to examine the closeness of association. The measured water quality parameters included pH, DO, temperature, conductivity, and TDS for in-situ and TSS, TP, TN, and chlorophyll A for ex-situ. The findings revealed morphometric changes among Midas cichlid species in Lake Batur caused by habitat and water quality differences. The distinction can be detected in the anterior and posterior bodies (C1, B1, C3, C6, C5, B3 and B4). Temperature and aquatic plants, Azolla pinnata, may detect the station and shape of fish in Lake Batur. Body shape cannot be identified by chlorophyll A, TN, DO, and TDS. Future genetic research could answer why fish groups with varied body types coexist in the same location.

WATER QUALITY PARAMETERS PREDICTION OF TIGRIS RIVER USING SENTINEL-2 DATA AND LASSO REGRESSION

Abstract. Water-related issues have become a growing concern due to the impact of human activities and climate change unpredictability, and Iraq faces a significant challenge with freshwater scarcity and poor quality. Field measurements are expensive, while remote sensing is a cost-effective alternative. This study aimed to monitor the water quality of the Tigris River in Baghdad using Sentinel-2 satellite images. The study employed the least absolute shrinkage and selection operator (LASSO) and field data from 14 different stations during 2018 and 2019 to measure water quality parameters, including temperature (Temp), electrical conductivity (Cond), total dissolved solids (TDS), potential of hydrogen (pH), turbidity (Turb), Chlorophyll-a (Chl_a), Blue-Green Algae (BGA), and Dissolved Oxygen (DO). The incorporation of spectral indices significantly improved the models’ effectiveness, with R2 greater than 0.8, except for Cond, which was 0.73. Water Quality Index (WQI) based on Iraqi standards was estimated and showed that the river water quality was categorized as poor and very poor. This approach can enhance water resource management and decisionmaking in areas where traditional monitoring approaches may be challenging and costly.

Water environment response of urban water networks in the Pearl River Delta (China) under the influence of typhoon rain events

Abstract Identifying water quality parameter concentrations and their drivers is important for the prevention and control of water environment pollution. In this study, we constructed an inverse model of water quality parameters based on measured water quality parameters and remote sensing spectral data for this study area using artificial neural networks. We investigated the water environment response of the urban water network in the Pearl River Delta under the influence of typhoon rain events and explored their spatial heterogeneity using a multiscale geographically weighted regression model. The results indicate that in regions with a high level of urbanization, the dissolved oxygen (DO) concentration in river water is lower, and the ammonia nitrogen (NH3-N) concentration is higher. Under the influence of typhoon rain events of varying intensities, the response of water quality parameters in the urban water network of Zhongshan City varies. The intensity of rainfall determines the impact of typhoon rain events on water quality parameter concentrations. Our results are expected to improve the understanding of water quality trends under the influence of typhoon rain events and help policymakers and planners better develop water environment control strategies during typhoon transit.

Suspected Legionella Transmission from a Single Donor to Two Lung Transplant Recipients — Pennsylvania, May 2022

In July 2022, the Pennsylvania Department of Health received two reports of laboratory-confirmed Legionnaires disease in patients who had recently received lung transplants from the same donor at a single Pennsylvania hospital. The donor’s cause of death was freshwater drowning in a river, raising suspicion of potential donor-derived transmission, because Legionella bacteria naturally live in fresh water. Further investigation of patients receiving other organs from the same donor did not identify additional legionellosis cases. Health care–associated infection caused by water exposure at the hospital was also evaluated as a potential source of infection and was found to be unlikely. Hospital water quality parameter measurements collected during May–June 2022 were within expected ranges and no water disruptions were noted, although no testing for Legionella was performed during this period. Notifiable disease data did not identify any other Legionnaires disease cases with exposure to this hospital within the 6 months before or after the two cases. Although laboratory testing did not confirm the source of recipient infections, available data suggest that the most likely source was the donor lungs. This cluster highlights the need for increased clinical awareness of possible infection with Legionella in recipients of lungs from donors who drowned in fresh water before organ recovery.

Analisis Komposisi Jenis dan Kelimpahan Zooplankton di Perairan Kampung Nafri, Kota Jayapura

This study aimed to determine the type, composition, and abundance of zooplankton in the waters of Kampung Nafri. Zooplankton were identified using zooplankton sample identification guidelines, and zooplankton abundance analysis was performed using the Sedgewick Rafter. Purposive sampling was used in this study. Zooplankton sampling was carried out horizontally on the surface of the water using a plankton net which was carried out in the morning around 08:00 - 10:30 WIT at 3 stations. Sampling at each station was done 2 times repetition and the water parameters were done 3 times repetition. In situ measurement of water quality parameters, such as salinity, pH, current speed, and temperature Based on the identification results, there are 11 types of zooplankton that inhabit the waters of Kampung Nafri. The highest value of zooplankton species composition in Nafri Waters was Naplius sp., which was 63%, and the lowest was Temora sp. and Corycaeus sp. by 1%. The highest abundance of zooplankton species in Nafri Waters was Nauplius sp. (Copepoda larvae), with a total abundance of 9,900 ind/l, and the lowest was Corycaeus sp. and Temora sp., with a total abundance of 200 ind/l.

Design And Development Of A Quality And Quantity Water Monitoring System For Water Tank Based On Internet Of Things

In the context of urban life, the quality and quantity of water stored in tanks play an indispensable role. However, concerns over the lack of effective monitoring of water conditions in tanks have garnered significant attention. This research aims to design a monitoring system utilizing Internet of Things (IoT) technology to ensure continuous monitoring of water quality and quantity within tanks.
 The study zeroes in on developing a solution that overcomes the limitations of traditional methods, known for their time and cost constraints. This solution hinges on a real-time monitoring system that integrates sensors and the NodeMCU ESP32 microcontroller. Measurements of water quality parameters, such as turbidity and total dissolved solids (TDS), along with assessments of water quantity through tank volume, are integrated into the system. Software development is carried out using the Arduino IDE platform.
 Through this research, an increased awareness of the importance of monitoring water quality in tanks is anticipated, and this solution is expected to make a significant contribution to the development of efficient and effective monitoring technology. Thus, a crucial step toward more accurate and up-to-date water monitoring in urban environments can be achieved.

Konsentrasi Limbah Pencemar MBAS (Methylen Blue Active Substance) pada Perairan Muara Kali Ijo, Kabupaten Kebumen

Muara Kali Ijo is the place where rivers flow in Kebumen Regency, which carry a lot of domestic wastes resulting from sanitation activities, namely detergent. The study aims to determine the quality of Muara Kali Ijo Waters based on MBAS concentration (Methylen Blue Active Substances). MBAS is a standard method for determining the concentration of anionic surfactants in detergents. This study uses descriptive methods with purposive random sampling techniques. Sampling was carried out on March 11, 2023 with a total of five stations. The results of the analysis of the MBAS concentration in the BBSPJPPI laboratory ranged from 0.031 – 0.064 mg/L and the measurement of water quality parameters was still relatively good, below the quality standard threshold. PCA results show that there is a negative correlation between MBAS concentration and water quality parameters. Productive anthropogenic activities around the area have a potential to contribute detergent waste from washing activities and increase MBAS concentrations.
 Keywords: antropogenic, muara kali ijo, MBAS, PCA, waters quality

Aquaculture 4.0: hybrid neural network multivariate water quality parameters forecasting model

This study examined the efficiency of hybrid deep neural network and multivariate water quality forecasting model in aquaculture ecosystem. Accurate forecasting of critical water quality parameters can allow for timely identification of possible problem areas and enable decision-makers to take pre-emptive remedial actions that can significantly improve water quality management in aquaculture industry. A novel hybrid deep learning neural network multivariate water quality parameters forecasting model is developed with the aid of ensemble empirical mode decomposition (EEMD) method, deep learning long-short term memory (LSTM) neural network (NN), and multivariate linear regression (MLR) method. The presented water quality forecasting model (shortened as EEMD–MLR–LSTM NN model) is developed using multivariate time-series water quality sensor data collected from Loch Duart company, a Salmon offshore aquaculture farm based around Scourie, northwest Scotland. The performance of the novel hybrid water quality forecasting model is validated by comparing the forecast result with measured water quality parameters data and the real Phytoplankton data count from the aquaculture farm. The forecast accuracy of the results suggests that the novel hybrid water quality forecasting model can be used as a valuable support tool for water quality management in aquaculture industries.

Development of River Flow and Water Quality Using IOT-based Smart Buoys Environment Monitoring System

Efficient and accurate river water quality monitoring is needed to support laboratory testing based on on-site sampling. Therefore, we have developed a monitoring system for river flow and water quality using sensor-equipped buoys and the Internet of Things (IoT) concept. An ESP32 NodeMCU microcontroller integrated with WiFi and compatible with Arduino IDE is used in the system. The buoy is equipped with GPS to determine the position and flow speed and sensors to measure water quality parameters of pH and temperature. Data on position, flow velocity, and water quality parameters are transmitted over a WiFi network using the MQTT protocol. The data is recorded by the buoy and uploaded and displayed on the adafruit.io platform. Positioning was done by comparing the values displayed on the Neo-6M GPS with the Maps application on the smartphone. The results show that the GPS coordinate values are accurate. The water quality parameter values obtained have an error rate of 3.3% for the pH sensor and 1.02% for the temperature sensor. Thus, the system we have developed has the potential to be used as a substitute for field sampling-based river water quality monitoring systems.

Suspected Legionella Transmission from a Single Donor to Two Lung Transplant Recipients - Pennsylvania, May 2022.

In July 2022, the Pennsylvania Department of Health received two reports of laboratory-confirmed Legionnaires disease in patients who had recently received lung transplants from the same donor at a single Pennsylvania hospital. The donor's cause of death was freshwater drowning in a river, raising suspicion of potential donor-derived transmission, because Legionella bacteria naturally live in fresh water. Further investigation of patients receiving other organs from the same donor did not identify additional legionellosis cases. Health care-associated infection caused by water exposure at the hospital was also evaluated as a potential source of infection and was found to be unlikely. Hospital water quality parameter measurements collected during May-June 2022 were within expected ranges and no water disruptions were noted, although no testing for Legionella was performed during this period. Notifiable disease data did not identify any other Legionnaires disease cases with exposure to this hospital within the 6 months before or after the two cases. Although laboratory testing did not confirm the source of recipient infections, available data suggest that the most likely source was the donor lungs. This cluster highlights the need for increased clinical awareness of possible infection with Legionella in recipients of lungs from donors who drowned in fresh water before organ recovery.

Evaluating the driving forces of spectral inversion methods used for assessing water quality parameters in Poyang Lake, China

AbstractWater quality parameters are key indicators of quality of water and can indicate the algal biomass and eutrophication in lakes. Therefore, this study spectrally inverted and evaluated the water quality of the Poyang Lake in China by analysing the differences between the measured water quality parameters and the observed image spectra of Sentinel‐2 remote sensing. This analysis was done using statistical regression models (SRMs) and various machine learning models (e.g., support vector machine [SVM] and random forest [RF]). The following major conclusions were drawn: (1) nutrients accumulated more in summer (June–August) than in winter (December–February). For example, in local areas of the main river, total nitrogen (TN) concentration reached 3.4 mg/L in summer of 2016, whereas total phosphorus (TP) concentrations were below 0.052 mg/L in winters of 2016 and 2017. (2) The three models, SRM, RF and SVM, achieved good results in the inversions of Secchi depth and permanganate index. However, differences were noted in the inversions of other parameters. For example, the goodness‐of‐fit (r2) between the inversion and measured values of TN concentration from RF was 0.81, while that from SR was 0.73. (3) The spatial distribution patterns of the water quality parameters showed differences. The ammoniacal nitrogen concentration was higher in the central region than that in the western region of the lake, whereas TP concentration was higher at the shoreline of the lake at 0.07 mg/L on 2 April 2017 but was relatively low in the main channel.

Assessment of Büyük Menderes River (West of the Türkiye) Surface Water Quality with Water Quality Index (WQI), Comprehensive Pollution Index (CPI) and Geographic Information Systems (GIS)

In the present study some of the water quality parameters were spatially examined with water quality and pollution indices in the Büyük Menderes River (BMR). In addition, the more effective parameters on the indices were determined among the parameters measured in the study. The measured water quality parameters were detected as WT:16.5-25.9 oC, pH:7.5-9.3, DO:nd-12.2 mgL-1, EC:312-30215 µScm-1, Salt:0.17-19.6 %o, NO2-N:nd-0.31 mgL-1, NO3-N:nd-1.08 mgL-1, NH4-N:0.035-25.2 mgL-1, TP:0.011-7.45 mgL-1, MBAS:nd-7.79 mgL-1 ve COD:nd-128.9 mgL-1. In the present study, several parameters were determined as the second class and third class of water quality according to the Turkish Water Pollution Control Regulation*. WQI value range was determined as from Bad (38.82) to Excellent (92.35), and CPI as from “Sub Clean (0.39) to Highly Polluted (9.62)” in the stream. It was determined that there was no compatibility between WQI and CPI used in determining the environmental risks in the study area. The GIS was found to be effective in interpreting the spatial distribution of the results obtained and in identifying the key areas that require control. Different statistical analyses were used to determine the relationships between variables. In multiple linear regression (MLR) analysis, it was determined that the most critical parameter affecting the indices was NH4-N. The results obtained from WQI and CPI in the present study indicate that anthropogenic activities are effective in the region. *:TWPCR, Quality criteria of inland surface water resources in terms of general chemical and physicochemical parameters by Class

Abundance and Biomass Analysis of Nostoc commune in Rice Field Habitat in Madura

Nostoc commune is often found in terrestrial habitats as well as aquatic habitats. Nostoc commune has the ability to fix nitrogen from the atmosphere, besides being used as food or medicine. Nostoc commune in Indonesia is still little utilized, this is because its existence is often misinterpreted as a weed in rice fields. The purpose of this study was to determine the abundance and biomass of Nostoc commune in rice field habitats. This research was conducted from 5 September 2022- September 23, 2022. The sampling method of Nostoc commune and water used was purposive sampling in the rice fields of Gilianyar Kamal Village, Bangkalan Regency, with three sampling location points. The measured water quality parameters include, nitrate, phosphate, water TOM, sediment TOM, and sediment C/N ratio. Nostoc commune data were identified to determine the biomass and abundance at each station. The results of the study of the abundance of Nostoc commune found that the first week of September and the second of September, respectively got an average of 695.1 colonies/m2 with a biomass of 1,576.2 g and 768.9 colonies/m2 with 1,799.7 g of biomass. Nostoc commune found in the rice fields is classified as abundant in each m2.

Measurement of Total Dissolved Solids and Total Suspended Solids in Water Systems: A Review of the Issues, Conventional, and Remote Sensing Techniques

This study provides a comprehensive review of the efforts utilized in the measurement of water quality parameters (WQPs) with a focus on total dissolved solids (TDS) and total suspended solids (TSS). The current method used in the measurement of TDS and TSS includes conventional field and gravimetric approaches. These methods are limited due to the associated cost and labor, and limited spatial coverages. Remote Sensing (RS) applications have, however, been used over the past few decades as an alternative to overcome these limitations. Although they also present underlying atmospheric interferences in images, radiometric and spectral resolution issues. Studies of these WQPs with RS, therefore, require the knowledge and utilization of the best mechanisms. The use of RS for retrieval of TDS, TSS, and their forms has been explored in many studies using images from airborne sensors onboard unmanned aerial vehicles (UAVs) and satellite sensors such as those onboard the Landsat, Sentinel-2, Aqua, and Terra platforms. The images and their spectral properties serve as inputs for deep learning analysis and statistical, and machine learning models. Methods used to retrieve these WQP measurements are dependent on the optical properties of the inland water bodies. While TSS is an optically active parameter, TDS is optically inactive with a low signal–noise ratio. The detection of TDS in the visible, near-infrared, and infrared bands is due to some process that (usually) co-occurs with changes in the TDS that is affecting a WQP that is optically active. This study revealed significant improvements in incorporating RS and conventional approaches in estimating WQPs. The findings reveal that improved spatiotemporal resolution has the potential to effectively detect changes in the WQPs. For effective monitoring of TDS and TSS using RS, we recommend employing atmospheric correction mechanisms to reduce image atmospheric interference, exploration of the fusion of optical and microwave bands, high-resolution hyperspectral images, utilization of ML and deep learning models, calibration and validation using observed data measured from conventional methods. Further studies could focus on the development of new technology and sensors using UAVs and satellite images to produce real-time in situ monitoring of TDS and TSS. The findings presented in this review aid in consolidating understanding and advancement of TDS and TSS measurements in a single repository thereby offering stakeholders, researchers, decision-makers, and regulatory bodies a go-to information resource to enhance their monitoring efforts and mitigation of water quality impairments.

A comparative assessment of the lagoons with water quality indexes and based on GIS: A study on the Aegean Sea and Mediterranean Sea

In this study, the current status of water quality in Güllük Lagoon and Köyceğiz-Dalyan Lagoon was examined by comparison using water quality indexes, multivariate statistical analyses and geographical information systems. Water quality parameters comprised of 9 variables i.e., WT, pH, DO, NO2-N, NO3-N, NH4-N, TP, SSM, BOD5 were measured in Güllük Lagoon and Köyceğiz-Dalyan Lagoon. Although there are important activities such as earthen pond fish farms, fish hatcheries, feldsbat and marble quarries, streams carrying domestic wastes, port, secondary residences and agricultural activities in Güllük Lagoon, there are intense tourism and agricultural activities in Köyceğiz-Dalyan Lagoon. The average concentrations of DO, TP, NO2-N results in Güllük Lagoon and DO, TP and NH4-N results in Köyceğiz-Dalyan Lagoon were determined in second class water quality according to surface water quality criteria. While both lagoons were found to be in “Good” quality class as a result of water quality index, Güllük Lagoon was found to be “medium polluted” and Köyceğiz-Dalyan Lagoon was found to be “slightly polluted” quality class as a result of comprehensive pollution index. It was observed that water quality index values of both lagoons decreased in the dry season, while their comprehensive pollution index values increased in the dry season. On the basis of the general averages of water quality index, it was found as Köyceğiz-Dalyan Lagoon (85.0) > Güllük Lagoon (84.05), and on the basis of the general averages of comprehensive pollution index, it was found as Güllük Lagoon (1.34) > Köyceğiz-Dalyan Lagoon (0.79). Relationships between variables were determined by geographical information systems (IDW technique) and statistical analyses (Descriptive statistics, Spearman rho correlation, Kruskal-Wallis test, multiple linear regression and Principal component analysis). As a result of multiple linear regression analysis in measured parameters, it was determined that the most important parameter affecting the water quality index in Güllük Lagoon was NH4-N, and the most important parameter affecting the comprehensive pollution index was SSM. In Köyceğiz-Dalyan Lagoon, it was observed that the water quality index was affected by the WT parameter and the comprehensive pollution index was affected by the SSM parameter. There is no difference in the concentrations of the average water quality parameters measured in both lagoons, and both lagoons are generally in the first and second class surface water quality class. However, Güllük Lagoon, which contains more different pollutant sources than Köyceğiz-Dalyan Lagoon, is shown to be more polluted according to water quality indexes. In addition, it has been determined that SSM is the most important parameter that determines the water quality among the measured water quality parameters of both lagoons.