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4 pages, 198 KiB

Open AccessEditorial

Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions

by Alessandro Bergamasco, Hong Quan Nguyen, Gabriella Caruso, Qianguo Xing and Eleonora Carol

Water 2021, 13(14), 1926; https://doi.org/10.3390/w13141926 - 13 Jul 2021

Cited by 5 | Viewed by 4443

Abstract

Coastal environments include several different habitat typologies, from shorelines to estuaries, and rocky and muddy environments [...] Full article

(This article belongs to the Special Issue Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions)

Research

Jump to: Editorial

11 pages, 4280 KiB

Open AccessArticle

Effects of Spatial Resolution on the Satellite Observation of Floating Macroalgae Blooms

by Xinhua Wang, Qianguo Xing, Deyu An, Ling Meng, Xiangyang Zheng, Bo Jiang and Hailong Liu

Water 2021, 13(13), 1761; https://doi.org/10.3390/w13131761 - 25 Jun 2021

Cited by 17 | Viewed by 2843

Abstract

Satellite images with different spatial resolutions are widely used in the observations of floating macroalgae booms in sea surface. In this study, semi-synchronous satellite images with different resolutions (10 m, 16 m, 30 m, 50 m, 100 m, 250 m and 500 m) [...] Read more.

Satellite images with different spatial resolutions are widely used in the observations of floating macroalgae booms in sea surface. In this study, semi-synchronous satellite images with different resolutions (10 m, 16 m, 30 m, 50 m, 100 m, 250 m and 500 m) acquired over the Yellow Sea, are used to quantitatively assess the effects of spatial resolution on the observation of floating macroalgae blooms of Ulva prolifera. Results indicate that the covering area of macroalgae-mixing pixels (MM-CA) detected from high resolution images is smaller than that from low resolution images; however, the area affected by macroalgae blooms (AA) is larger in high resolution images than in low resolution ones. The omission rates in the MM-CA and the AA increase with the decrease of spatial resolution. These results indicate that satellite remote sensing on the basis of low resolution images (especially, 100 m, 250 m, 500 m), would overestimate the covering area of macroalgae while omit the small patches in the affected zones. To reduce the impacts of overestimation and omission, high resolution satellite images are used to show the seasonal changes of macroalgae blooms in 2018 and 2019 in the Yellow Sea. Full article

(This article belongs to the Special Issue Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions)

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20 pages, 5387 KiB

Open AccessArticle

Discovering Water Quality Changes and Patterns of the Endangered Thi Vai Estuary in Southern Vietnam through Trend and Multivariate Analysis

by Malte Lorenz, Hong Quan Nguyen, Trong Dieu Hien Le, Stephanie Zeunert, Duc Huy Dang, Quang Dung Le, Huyen Le and Günter Meon

Water 2021, 13(10), 1330; https://doi.org/10.3390/w13101330 - 11 May 2021

Cited by 7 | Viewed by 4725

Abstract

Temporal and spatial water quality data are essential to evaluate human health risks. Understanding the interlinking variations between water quality and socio-economic development is the key for integrated pollution management. In this study, we applied several multivariate approaches, including trend analysis, cluster analysis, [...] Read more.

Temporal and spatial water quality data are essential to evaluate human health risks. Understanding the interlinking variations between water quality and socio-economic development is the key for integrated pollution management. In this study, we applied several multivariate approaches, including trend analysis, cluster analysis, and principal component analysis, to a 15-year dataset of water quality monitoring (1999 to 2013) in the Thi Vai estuary, Southern Vietnam. We discovered a rapid improvement for most of the considered water quality parameters (e.g., DO, NH₄, and BOD) by step trend analysis, after the pollution abatement in 2008. Nevertheless, the nitrate concentration increased significantly at the upper and middle parts and decreased at the lower part of the estuary. Principal component (PC) analysis indicates that nowadays the water quality of the Thi Vai is influenced by point and diffuse pollution. The first PC represents soil erosion and stormwater loads in the catchment (TSS, PO₄, and Fe_total); the second PC (DO, NO₂, and NO₃) determines the influence of DO on nitrification and denitrification; and the third PC (pH and NH₄) determines point source pollution and dilution by seawater. Therefore, this study demonstrated the need for stricter pollution abatement strategies to restore and to manage the water quality of the Thi Vai Estuary. Full article

(This article belongs to the Special Issue Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions)

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22 pages, 3514 KiB

Open AccessArticle

Linking Microbial Functioning and Trophic Pathways to Ecological Status in a Coastal Mediterranean Ecosystem

by Franco Decembrini, Carmela Caroppo, Gabriella Caruso and Alessandro Bergamasco

Water 2021, 13(9), 1325; https://doi.org/10.3390/w13091325 - 10 May 2021

Cited by 9 | Viewed by 3596

Abstract

Coastal marine ecosystems host complex microbial communities whose composition and metabolism are influenced by continental inputs and mesoscale properties of seawater masses. The identifying traits of the phytoplankton and bacteria such as biomass, size, shape and their metabolism related to organic matter production [...] Read more.

Coastal marine ecosystems host complex microbial communities whose composition and metabolism are influenced by continental inputs and mesoscale properties of seawater masses. The identifying traits of the phytoplankton and bacteria such as biomass, size, shape and their metabolism related to organic matter production and degradation, recognized as indicators of the functioning of an ecosystem, were observed in the Gulf of Manfredonia (South Adriatic Sea, Italy) in late spring. This Gulf area is characterized by terrestrial inputs and mesoscale circulation influence such as coastal waters flowing southward from the North Adriatic and offshore waters interested by the Ionian Sea. Water samples were grouped in clusters (Coastal, Intermediate, Offshore and Deep Systems) according to the water column properties. Phytoplankton community biomass and composition, autotrophic and total prokaryotic abundances and microbial metabolism such as enzyme activity rates and prokaryotic heterotrophic production were analyzed to elucidate the trophic pathways with the objective to infer on the ecosystem status. As expected, size-fractionated phytoplankton biomass and production showed greater concentration in coastal waters with prevalence of the largest fractions (micro- and nano-) supported by the diatoms. Conversely, lower biomass and production were measured in all off-shore waters, mainly sustained by smallest fractions (nano-sized phytoflagellates and picophytoplankton). Total and autotrophic prokaryotic abundance decreased from coastal to offshore stations, inversely with respect to cell volume. Prokaryotic heterotrophic production was just below 50% compared to that of phytoplankton in all waters, evidencing an active biomass synthesis. High alkaline phosphatase and leucine aminopeptidase in coastal and offshore waters suggested the quick regeneration of Phosphorus and protein decomposition, respectively. Different levels of phytoplankton-bacteria association might provide a tool to define the ecological status of the studied system in the observed period; an approach to ecosystem assessment exportable to other coastal systems is proposed. Full article

(This article belongs to the Special Issue Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions)

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16 pages, 2699 KiB

Open AccessArticle

Intestinal Microbial Ecology and Fillet Metal Chemistry of Wild Grey Mullets Reflect the Variability of the Aquatic Environment in a Western Mediterranean Coastal Lagoon (Santa Giusta, Sardinia, Italy)

by Rosanna Floris, Gabriele Sanna, Cecilia Teodora Satta, Carlo Piga, Francesco Sanna, Antonella Lugliè and Nicola Fois

Water 2021, 13(6), 879; https://doi.org/10.3390/w13060879 - 23 Mar 2021

Cited by 6 | Viewed by 3149

Abstract

Fish populations play an active role in the maintenance of aquatic ecosystems biodiversity. Their intestinal microbiota and fillet chemistry depend on abiotic and biotic factors of the water environments that they inhabit. The present study investigated the grey mullets’ gut microbiota from a [...] Read more.

Fish populations play an active role in the maintenance of aquatic ecosystems biodiversity. Their intestinal microbiota and fillet chemistry depend on abiotic and biotic factors of the water environments that they inhabit. The present study investigated the grey mullets’ gut microbiota from a transitional aquatic ecosystem (Santa Giusta Lagoon, Sardinia, Italy) by a multidisciplinary approach which refers the results of (1) gut cultivable microbiota analyses (MA), (2) the trace metal assessment of fish muscle (TM), (3) the physico-chemical water monitoring (PC). MA detected the greatest number of total aerobic heterotrophic bacteria, Enterobacteriaceae and coliforms in Autumn (mean values 1.3 × 10⁵, 2.4 × 10⁴, 1.1 × 10⁴ cfu g⁻¹, respectively) when the accumulated rain and mean values of nutrients (reactive phosphorous and silica) were the highest. Marine bacteria were more numerous in Summer (mean value 7.4 × 10⁵ cfu g⁻¹) when the highest mean values of water temperature and salinity were registered. The gut bacteria were identified as Pseudomonas spp. (64%), Aeromonas spp. (17%), Ochrobactrum pseudogrignonense (10%), Providencia spp. (5%), Enterobacter ludwigii (2%) and Kocuria tytonicola (2%). TM showed that Ca, Na, B and Ni increased their concentrations in Winter while maxima of P, Zn, Cu and Fe were found in muscles of fish sampled in Summer. This study highlighted that the fish intestinal microbiota and metal composition of the fillet reflected the seasonal aquatic environmental variability. Full article

(This article belongs to the Special Issue Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions)

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16 pages, 3211 KiB

Open AccessArticle

Research on Inversion Mechanism of Chlorophyll—A Concentration in Water Bodies Using a Convolutional Neural Network Model

by Yun Xue, Lei Zhu, Bin Zou, Yi-min Wen, Yue-hong Long and Song-lin Zhou

Water 2021, 13(5), 664; https://doi.org/10.3390/w13050664 - 28 Feb 2021

Cited by 16 | Viewed by 4061

Abstract

For Case-II water bodies with relatively complex water qualities, it is challenging to establish a chlorophyll-a concentration (Chl-a concentration) inversion model with strong applicability and high accuracy. Convolutional Neural Network (CNN) shows excellent performance in image target recognition and natural language processing. However, [...] Read more.

For Case-II water bodies with relatively complex water qualities, it is challenging to establish a chlorophyll-a concentration (Chl-a concentration) inversion model with strong applicability and high accuracy. Convolutional Neural Network (CNN) shows excellent performance in image target recognition and natural language processing. However, there little research exists on the inversion of Chl-a concentration in water using convolutional neural networks. Taking China’s Dongting Lake as an example, 90 water samples and their spectra were collected in this study. Using eight combinations as independent variables and Chl-a concentration as the dependent variable, a CNN model was constructed to invert Chl-a concentration. The results showed that: (1) The CNN model of the original spectrum has a worse inversion effect than the CNN model of the preprocessed spectrum. The determination coefficient (R_P²) of the predicted sample is increased from 0.79 to 0.88, and the root mean square error (RMSE_P) of the predicted sample is reduced from 0.61 to 0.49, indicating that preprocessing can significantly improve the inversion effect of the model.; (2) among the combined models, the CNN model with Baseline1_SC (strong correlation factor of 500–750 nm baseline) has the best effect, with R_P² reaching 0.90 and RMSEP only 0.45. The average inversion effect of the eight CNN models is better. The average R_P² reaches 0.86 and the RMSE_P is only 0.52, indicating the feasibility of applying CNN to Chl-a concentration inversion modeling; (3) the performance of the CNN model (Baseline1_SC (R_P² = 0.90, RMSE_P = 0.45)) was far better than the traditional model of the same combination, i.e., the linear regression model (R_P² = 0.61, RMSE_P = 0.72) and partial least squares regression model (Baseline1_SC (R_P² = 0.58. RMSE_P = 0.95)), indicating the superiority of the convolutional neural network inversion modeling of water body Chl-a concentration. Full article

(This article belongs to the Special Issue Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions)

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13 pages, 3146 KiB

Open AccessFeature PaperArticle

Evaluating Traditional Empirical Models and BPNN Models in Monitoring the Concentrations of Chlorophyll-A and Total Suspended Particulate of Eutrophic and Turbid Waters

by Bo Jiang, Hailong Liu, Qianguo Xing, Jiannan Cai, Xiangyang Zheng, Lin Li, Sisi Liu, Zhiming Zheng, Huiyan Xu and Ling Meng

Water 2021, 13(5), 650; https://doi.org/10.3390/w13050650 - 28 Feb 2021

Cited by 21 | Viewed by 3385

Abstract

In order to use in situ sensed reflectance to monitor the concentrations of chlorophyll-a (Chl-a) and total suspended particulate (TSP) of waters in the Pearl River Delta, which is featured by the highly developed network of rivers, channels and ponds, 135 sets of [...] Read more.

In order to use in situ sensed reflectance to monitor the concentrations of chlorophyll-a (Chl-a) and total suspended particulate (TSP) of waters in the Pearl River Delta, which is featured by the highly developed network of rivers, channels and ponds, 135 sets of simultaneously collected water samples and reflectance were used to test the performance of the traditional empirical models (band ratio, three bands) and the machine learning models of a back-propagation neural network (BPNN). The results of the laboratory analysis with the water samples show that the Chl-a ranges from 3 to 256 µg·L⁻¹ with an average of 39 µg·L⁻¹ while the TSP ranges from 8 to 162 mg·L⁻¹ and averages 42.5 mg·L⁻¹. Ninety sets of 135 samples are used as training data to develop the retrieval models, and the remaining ones are used to validate the models. The results show that the proposed band ratio models, the three-band combination models, and the corresponding BPNN models are generally successful in estimating the Chl-a and the TSP, and the mean relative error (MRE) can be lower than 30% and 25%, respectively. However, the BPNN models have no better performance than the traditional empirical models, e.g., in the estimation of TSP on the basis of the reflectance at 555 and 750 nm (R555 and R750, respectively), the model of BPNN (R555, R750) has an MRE of 23.91%, larger than that of the R750/R555 model. These results suggest that these traditional empirical models are usable in monitoring the optically active water quality parameters of Chl-a and TSP for eutrophic and turbid waters, while the machine learning models have no significant advantages, especially when the cost of training samples is considered. To improve the performance of machine learning models in future applications on the basis of ground sensor networks, large datasets covering various water situations and optimization of input variables of band configuration should be strengthened. Full article

(This article belongs to the Special Issue Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions)

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32 pages, 17722 KiB

Open AccessFeature PaperArticle

Groundwater Monitoring Systems to Understand Sea Water Intrusion Dynamics in the Mediterranean: The Neretva Valley and the Southern Venice Coastal Aquifers Case Studies

by Ivan Lovrinović, Alessandro Bergamasco, Veljko Srzić, Chiara Cavallina, Danko Holjević, Sandra Donnici, Joško Erceg, Luca Zaggia and Luigi Tosi

Water 2021, 13(4), 561; https://doi.org/10.3390/w13040561 - 23 Feb 2021

Cited by 22 | Viewed by 5101

Abstract

Sea water intrusion (SWI) has been widely recognized as a global problem, significantly influencing coastal aquifers, mostly through reduced water quality and agricultural production indicators. In this paper, we present the outcomes of the implementation of two independent real-time monitoring systems, planned and [...] Read more.

Sea water intrusion (SWI) has been widely recognized as a global problem, significantly influencing coastal aquifers, mostly through reduced water quality and agricultural production indicators. In this paper, we present the outcomes of the implementation of two independent real-time monitoring systems, planned and installed to get insights on groundwater dynamics within the adjacent coastal aquifer systems, one located in the Neretva Valley, southeastern Croatia, the other located south of the Venice lagoon, northeastern Italy. Both systems are presented with technical details and the capacity to observe, store, and transmit (Neretva site) observed values in real-time. Analysis of time series reveals the significant influence of the sea level oscillations onto the observed groundwater electrical conductivity (EC) and piezometric head values, while precipitation rate is detected as a driving mechanism for groundwater parameters in shallow geological units. The installed monitoring systems are shown to be of great importance to provide qualitative and quantitative information on the processes influencing groundwater and surface water dynamics within two coastal systems. Full article

(This article belongs to the Special Issue Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions)

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15 pages, 7162 KiB

Open AccessArticle

Using Satellite Remote Sensing to Study the Effect of Sand Excavation on the Suspended Sediment in the Hong Kong-Zhuhai-Macau Bridge Region

by Fenfen Liu, Tonghui Zhang, Haibin Ye and Shilin Tang

Water 2021, 13(4), 435; https://doi.org/10.3390/w13040435 - 7 Feb 2021

Cited by 7 | Viewed by 3733

Abstract

The Hong Kong-Zhuhai-Macau Bridge crosses the Pearl River Estuary and is the largest bridge and tunnel project in the world. During the construction period of this project, the excessive suspended sediment was found in the construction region. The suspended sediment generated by sand [...] Read more.

The Hong Kong-Zhuhai-Macau Bridge crosses the Pearl River Estuary and is the largest bridge and tunnel project in the world. During the construction period of this project, the excessive suspended sediment was found in the construction region. The suspended sediment generated by sand excavation in the upstream was assumed to have a significant impact on the suspended sediment in the tunnel region. In this study, we assessed the impact of upstream sand excavation on the suspended sediment in the Hong Kong-Zhuhai-Macau Bridge construction area using Landsat OLI, ETM+, and TM data. Regional suspended sediment algorithms were developed for Landsat using a symbolic regression method based on data from in situ measurements in the study area from 2003 to 2014. A band shift was conducted on the remote sensing reflectance data from Landsat ETM+ and OLI to produce a time series of the suspended sediment concentrations that was internally consistent with that of the Landsat TM data. The suspended sediment distribution was extracted and used to compare under two different conditions, with and without sand excavation. The correlations of the time series of the suspended sediment concentrations in different regions in the surrounding waters, including the correlations between the construction regions and the sand excavation regions, were calculated. Our results indicated that the sand excavation north of the Pearl River Estuary had a limited impact on the surface suspended sediment concentrations in the Hong Kong-Zhuhai-Macau Bridge tunnel area. Full article

(This article belongs to the Special Issue Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions)

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16 pages, 3943 KiB

Open AccessArticle

Identification of the Origins of Vadose-Zone Salinity on an Agricultural Site in the Venice Coastland by Ionic Molar Ratio Analysis

by Ester Zancanaro, Pietro Teatini, Elia Scudiero and Francesco Morari

Water 2020, 12(12), 3363; https://doi.org/10.3390/w12123363 - 30 Nov 2020

Cited by 8 | Viewed by 2305

Abstract

Saltwater contamination seriously affects water quality and land productivity of reclaimed farmlands along the Venice Lagoon, Italy. To characterize the hydrogeochemical dynamics involved in this phenomenon, a three-year study was carried out in an experimental field located at the southern margin of the [...] Read more.

Saltwater contamination seriously affects water quality and land productivity of reclaimed farmlands along the Venice Lagoon, Italy. To characterize the hydrogeochemical dynamics involved in this phenomenon, a three-year study was carried out in an experimental field located at the southern margin of the Venice Lagoon. Soil matric potential, quality of soil pore water and groundwater, and soil physical and chemical properties were monitored at five monitoring stations. Relationships between Cl⁻, Na⁺, Mg^2+, Ca²⁺, K⁺, SO₄²⁻, Br⁻ ionic concentrations, and electrical conductivity of the water samples with the soil characteristics (e.g., texture, exchangeable cations) were investigated. Soil water flux direction was calculated and related to ion concentrations. Moreover, specific molar ratios (Mg/Ca, Na/Cl, Cl/Br, and SO₄/Cl) were calculated to identify the main drivers affecting salinity in the field. The study confirmed that the experimental site was strongly affected by soil and water salinity, and two major contamination dynamics were identified. The first one was mainly driven by seawater intrusion from the near lagoon and salty watercourses, while the second was derived by the interactions between the peaty soil and salts that were originally in place, since the area was only reclaimed a few decades ago. The latter highlighted the potentiality of the experimental field to become an acidic sulfate environment. Ionic ratios were implemented and proved to be an important tool for the identification of salinity origin. Full article

(This article belongs to the Special Issue Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions)

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17 pages, 2760 KiB

Open AccessArticle

Occurrence and Distribution of UV Filters in Beach Sediments of the Southern Baltic Sea Coast

by Aleksander Astel, Marcin Stec and Iwona Rykowska

Water 2020, 12(11), 3024; https://doi.org/10.3390/w12113024 - 28 Oct 2020

Cited by 41 | Viewed by 4785

Abstract

The interest in UV filters’ occurrence in the environment has increased since they were recognized as “emerging contaminants” having potentially adverse impacts on many ecosystems and organisms. Increased worldwide demand for sunscreens is associated with temperature anomalies, high irradiance, and changes in the [...] Read more.

The interest in UV filters’ occurrence in the environment has increased since they were recognized as “emerging contaminants” having potentially adverse impacts on many ecosystems and organisms. Increased worldwide demand for sunscreens is associated with temperature anomalies, high irradiance, and changes in the tourist market. Recently, it has been demonstrated that personal care products, including sunscreens, appear in various ecosystems and geographic locations causing an ecotoxicological threat. Our goal was to determine for the first time the presence of selected organic UV filters at four beaches in the central Pomeranian region in northern Poland and to assess their horizontal and vertical distribution as well as temporal variation at different locations according to the touristic pressure. In this pioneering study, the concentration of five UV filters was measured in core sediments dredged from four exposed beaches (Darłowo, Ustka, Rowy, and Czołpino). UV filters were detected in 89.6% of collected cores at detection frequencies of 0–22.2%, 75–100%, 0–16.7%, and 2.8–25% for benzophenone-1 (BP-1), benzophenone-2 (BP-2), benzophenone-3 (BP-3), and enzacamene (4-MBC), respectively. In terms of seasonality, the concentration of UV filters generally increased in the following order: summer > autumn > spring. No detectable levels of 3-BC (also known as 3-benzylidene camphor) were recorded. No differences were found in the concentration of UV filters according to the depth of the sediment core. During the summer and autumn seasons, all UV filters were detected in higher concentrations in the bathing area or close to the waterline than halfway or further up the beach. Results presented in this study demonstrate that the Baltic Sea coast is not free from UV filters. Even if actual concentrations can be quantified as ng·kg⁻¹ causing limited environmental threat, much higher future levels are expected due to the Earth’s principal climatic zones shifting northward. Full article

(This article belongs to the Special Issue Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions)

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21 pages, 5733 KiB

Open AccessArticle

An Improved Model for Chlorophyll-a Concentration Retrieval in Coastal Waters Based on UAV-Borne Hyperspectral Imagery: A Case Study in Qingdao, China

by Yingying Gai, Dingfeng Yu, Yan Zhou, Lei Yang, Chao Chen and Jun Chen

Water 2020, 12(10), 2769; https://doi.org/10.3390/w12102769 - 5 Oct 2020

Cited by 25 | Viewed by 3481

Abstract

Chlorophyll-a (Chl-a) is an objective biological indicator, which reflects the nutritional status of coastal waters. However, the turbid coastal waters pose challenges to the application of existing Chl-a remote sensing models of case II waters. Based on the bio-optical models, we analyzed the [...] Read more.

Chlorophyll-a (Chl-a) is an objective biological indicator, which reflects the nutritional status of coastal waters. However, the turbid coastal waters pose challenges to the application of existing Chl-a remote sensing models of case II waters. Based on the bio-optical models, we analyzed the suppression of coastal total suspended matter (TSM) on the Chl-a optical characteristics and developed an improved model using the imagery from a hyper-spectrometer mounted on an unmanned aerial vehicle (UAV). The new model was applied to estimate the spatiotemporal distribution of Chl-a concentration in coastal waters of Qingdao on 17 December 2018, 22 March 2019, and 20 July 2019. Compared with the previous models, the correlation coefficients (

R^{2}

) of Chl-a concentrations retrieved by the new model and in situ measurements were greatly improved, proving that the new model shows a better performance in retrieving coastal Chl-a concentration. On this basis, the spatiotemporal variations of Chl-a in Qingdao coastal waters were analyzed, showing that the spatial variation is mainly related to the TSM concentration, wind waves, and aquaculture, and the temporal variation is mainly influenced by the sea surface temperature (SST), sea surface salinity (SSS), and human activities. Full article

(This article belongs to the Special Issue Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions)

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18 pages, 2999 KiB

Open AccessEditor’s ChoiceArticle

Seasonal Variation of Dissolved Oxygen in the Southeast of the Pearl River Estuary

by Guangping Liu, Weihong He and Shuqun Cai

Water 2020, 12(9), 2475; https://doi.org/10.3390/w12092475 - 3 Sep 2020

Cited by 29 | Viewed by 6379

Abstract

Dissolved oxygen (DO) concentration in estuaries is highly variable at different spatial and temporal scales, which is affected by physical, chemical and biological processes. This study analyzed the spatial–temporal distributions of dissolved oxygen concentration and bottom hypoxia in the southeast of the Pearl [...] Read more.

Dissolved oxygen (DO) concentration in estuaries is highly variable at different spatial and temporal scales, which is affected by physical, chemical and biological processes. This study analyzed the spatial–temporal distributions of dissolved oxygen concentration and bottom hypoxia in the southeast of the Pearl River Estuary (PRE) using monthly water quality monitoring and hydrographic data covering the period 2000–2017. The seasonal spatial–temporal variation of DO concentration was studied using various methods, such as rotated empirical orthogonal functions, harmonic analysis, and correlation analysis. The results showed that DO stratification was significant in summer, but it was not distinct in winter, during which DO concentration peaked. DO stratification exhibited a significantly positive correlation with water stratification. In the south and west of Hong Kong (SHK and WHK, respectively), DO concentration fields exhibited distinct seasonal changes in the recent 18 years. In SHK, the main periods of the surface DO variation were 24, 12, and 6 months, whereas the main period was 12 months in WHK. The main period of the bottom DO variation was 12 months in both SHK and WHK. In SHK, the spatial–temporal variations in surface and bottom DO were highly related to the variations of salinity, dissolved inorganic nitrogen (DIN), and active phosphorus, and the variation of surface DO was also connected to the variation of temperature and chlorophyll a. In WHK, the variations in surface and bottom DO were highly related to the variations of salinity and temperature, and the variation of surface DO was also connected to the variation of DIN. The river discharge and wind had a different important influence on the temporal variability of DO in WHK and SHK. These findings suggested that the variations of DO may be controlled by coupled physical and biochemical processes in the southeast of PRE. From 2000 to 2017, bottom hypoxia in the southeast of PRE occurred in the summers of 7 years. SHK appeared to be more vulnerable to hypoxia than WHK. Full article

(This article belongs to the Special Issue Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions)

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13 pages, 3559 KiB

Open AccessArticle

Microcystis Bloom in an Urban Lake after River Water Diversion—A Case Study

by Xiaoyan Chen, Dong Bai, Chunlei Song, Yiyong Zhou and Xiuyun Cao

Water 2020, 12(6), 1811; https://doi.org/10.3390/w12061811 - 24 Jun 2020

Cited by 7 | Viewed by 3360

Abstract

To improve the water quality of Lake Yuehu, a water diversion from the Han River was conducted in July 2008. However, an unexpected Microcystis bloom occurred in the lake after water introduction. Water and sediment samples were collected from Lake Yuehu and the [...] Read more.

To improve the water quality of Lake Yuehu, a water diversion from the Han River was conducted in July 2008. However, an unexpected Microcystis bloom occurred in the lake after water introduction. Water and sediment samples were collected from Lake Yuehu and the variation of chemical and biochemical parameters, as well as the phytoplankton community, were analyzed during the water diversion to assess its effect and to clarify the mechanism leading to the Microcystis bloom. The nitrogen (N) concentration was increased and phosphorus (P) concentration decreased in Lake Yuehu after receiving water from the Han River, which had a high loading of N and a low loading of P. These conditions may benefit the growth and dominance of non-N₂ fixing Microcystis, as it may not have suffered from P limitation during our study because it did not produce extracellular phosphatase, which worked as an indicator of P deficiency, as evidenced by the in situ enzyme-labelled fluorescence. Notably, the sediment Fe (OOH)~P content significantly decreased in Lake Yuehu; this pulsed release of P from the sediment might have sustained the Microcystis bloom. Based on our results, algal blooms may occur as a consequence of conducting water diversion projects to improve water quality. Full article

(This article belongs to the Special Issue Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions)

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16 pages, 7019 KiB

Open AccessArticle

Quantile Analysis of Long-Term Trends of Near-Surface Chlorophyll-a in the Pearl River Plume

by Na Gao, Yi Ma, Mingli Zhao, Li Zhang, Haigang Zhan, Shuqun Cai and Qingyou He

Water 2020, 12(6), 1662; https://doi.org/10.3390/w12061662 - 10 Jun 2020

Cited by 21 | Viewed by 3416

Abstract

The concentration of chlorophyll-a (CHL) is an important proxy for the amount of phytoplankton biomass in the ocean. Characterizing the variability of CHL in the Pearl River Plume (PRP) is therefore of great importance for the understanding of the changes in oceanic [...] Read more.

The concentration of chlorophyll-a (CHL) is an important proxy for the amount of phytoplankton biomass in the ocean. Characterizing the variability of CHL in the Pearl River Plume (PRP) is therefore of great importance for the understanding of the changes in oceanic productivity in the coastal region. By applying quantile regression analysis on 21-year (1998–2018) near-surface CHL data from satellite observations, this study investigated the long-term trend of CHL in the PRP. The results show decreasing trends (at an order of 10⁻² mg m⁻³ year⁻¹) for all percentiles of the CHL in the PRP, suggesting a decrease in productivity in the past two decades. The trends differ fundamentally from those in the open regions of the northern South China Sea with mixed signs and small magnitudes (10⁻⁴ mg m⁻³ year⁻¹). The magnitudes of the trends in high quantiles (>80th) are larger than those in low quantiles (<50th) in the PRP, indicative of a decrease in the variance of the CHL. The area with apparent decreasing trends is restricted to the PRP in summer and extends to the entire coastal region in winter. This decrease in CHL is possibly attributed to the decrease in nutrient input from the river runoff and the weakening of wind-forced mixing rather than the changes in sea surface temperature. This study extends our knowledge on the variability of CHL in the PRP and provides references to the investigation of the changes of the coastal ecological environment. Full article

(This article belongs to the Special Issue Advances in Water Quality Monitoring and Assessment in Marine and Coastal Regions)

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