High Chl-a Concentrations Research Articles

Two-decade variability and trend of chlorophyll-a in the Arabian Sea and Persian Gulf based on reconstructed satellite data

The spatiotemporal variability of chlorophyll-a (Chl-a) in the Arabian Sea (AS) and Persian Gulf (PG) has been widely studied, but long-term trends and influencing factors remain less understood due to data gaps. This study investigates Chl-a variability and trends from 2001 to 2019 using reconstructed MODIS-Terra monthly Chl-a and sea surface temperature (SST) data, employing the Data Interpolating Empirical Orthogonal Functions (DINEOF) method for high-accuracy reconstruction. Results reveal pronounced seasonal variability, with Chl-a peaks exceeding 3 mg m-3 during southwestern monsoons and ranging between 1–3 mg m-3 during northeastern monsoons, with the lowest levels in transitional months. Spatially, the highest Chl-a concentrations were observed in the western and northeastern AS, influenced by summer southwestern (SW) and winter northeastern (NE) monsoons. Trend analysis using Sen’s slope and the Mann-Kendall test indicates significant Chl-a declines (-0.002 to 0) along ASPG coasts, with slight increases (~0.005) in the southeastern AS and southern PG. Rising SST anomalies (SST_A) correlated with reduced Chl-a anomalies (Chl-a_A) in the western AS, while increased wind anomalies (Wind_A) enhanced Chl-a_A in the western AS but decreased it in the southern PG. These findings enhance our understanding of the complex environmental dynamics shaping the ASPG ecosystems.

Chlorophyll-a interannual and seasonal variability in Panay Gulf: Identification of potential productive sites in the municipal waters and offshore blooms aided by water currents

Chlorophyll-a (Chl-a) is often used as a substitute for marine primary productivity measurements in fishing grounds. Panay Gulf stands as one of the Philippines’ vital fishing grounds, however, there are limited studies on its Chl-a interannual and seasonal variability. As such, this study used remotely sensed Chl-a data from 2017 to 2023 to assess areas with high Chl-a concentrations, and high primary productivity. The relationship of Chl-a to location, month, year, and water current variables was evaluated using a generalized additive model (GAM). Chl-a value of >10 mg.m−3 was observed approximately <6.5, <2 km, and <1 km from the coast of Negros, Guimaras, and Panay Island respectively. During the Northeast Monsoon, short-term offshore pockets with elevated Chl-a levels were noted 13–24 km from the coast of Binalbagan, Negros Occidental that function as brief feeding grounds for marine organisms. These Chl-a pockets originated from the coast of Negros Occidental and were advected by the water currents to the center of the gulf. Furthermore, 2017 and 2022 have the highest Chl-a value in Panay Gulf, coinciding with the region's seasonal high fisheries production. Major peaks were regularly observed in January and December when offshore Chl-a pockets were present. A minor peak was observed in July corresponding to the Southwest Monsoon season and attributed to summer blooms. The lowest Chl-a values were observed in September during the transition months. Furthermore, high Chl-a values were found in low current speed near the coast and water moving west and southwest during the Northeast Monsoon. This study is the first to evaluate the Chl-a dynamics in Panay Gulf, which is valuable information to understand the influence of the environment on marine productivity. This study may prompt the local government to intensify monitoring efforts and coastal protection in these valuable areas within the municipal waters.

Spatial and seasonal variability of chlorophyll-a, total suspended matter, and colored dissolved organic matter in the Sundarban mangrove forest using earth observation and field data

The Sundarbans, the world's largest mangrove forest, confronts potential threats from various anthropogenic activities leading to degradation of its aquatic ecosystem. To examine the current status of the aquatic ecosystem, this study aimed to evaluate the spatial and seasonal fluctuation of three principal water quality attributes namely Chlorophyll-a (Chl-a), Total Suspended Matter (TSM), and Colored Dissolved Organic Matter (CDOM) in the complex tidal river systems of the Sundarban mangroves forest using earth observation and in-situ data. A set of two bio-optical algorithms, Ocean color-2 (OC-2) and Ocean color-3 (OC-3), were applied to measure Chl-a concentration, Green/NIR and the Red/NIR band ratio algorithms were used for TSM and the Case-2 Regional Coast Color (C2RCC) processor in the SNAP software was applied to obtain CDOM concentration in study area. A total of 50 in-situ samples were collected during post-monsoon and pre-monsoon to validate the results. Our results clearly demonstrated seasonal variability with higher Chl-a concentrations in post-monsoon than pre-monsoon. This was due to the OC-2 algorithm which produced better results with R2 = 0.73, RMSE = 0.27 for post-monsoon and R2 = 0.55, RMSE = 0.32 for pre-monsoon. Whilst, TSM concentration performed the best with R2 = 0.77; RMSE = 15.82 and R2 = 0.65; RMSE = 33.96 in post-monsoon and pre-monsoon according to the Green/NIR band ratio method. The nearshore and narrow waterway regions had the highest concentrations of TSM and Chl-a, whereas the offshore regions had the lowest. Strong association were observed between the in-situ and satellite derive absorption coefficient, aCDOM (m−1). The R2 for a CDOM during pre-monsoon was 0.65 and throughout the post-monsoon, it was 0.74. Pre-monsoon concentrations were found to be higher due to marine sources and higher wind speeds, possibly due to sediment resuspension. This kind of baseline evaluation will help to detect threats, direct preventive measures for the protection of biodiversity, and deepen our knowledge of these distinct ecosystems. The results will help develop flexible management and preservation plans that can adjust to both natural and man-made changes.

Spatial patterns in chlorophyll a concentration during the winter–spring periods in the Barents Sea

Climatic fluctuations have been documented to strongly affect Arctic marine ecosystems. Plankton assemblages serve as the most sensitive indicators of such environmental forcing. We conducted a study to investigate the spatial variability of chlorophyll a (Chl-a) concentration during two pre-bloom periods (March–April 2021 and February–March 2022) in relation to the distribution of different water masses and associated properties. The upper 50 m layer of the water column was homogeneous and stable, characterized by high nutrient concentrations. Our mapping of the Barents Sea based on Chl-a concentrations revealed low estimates during the winter period. In contrast, two distinct Chl-a peaks were observed in the spring. The first region with high Chl-a concentrations was identified in Murmansk Coastal Water and Atlantic Water (0.7–1.4 mg m−3), reflecting the positive impact of the frontal zone between these interacting water masses. The second region with elevated Chl-a concentrations (0.9–1.1 mg m−3) was located in Kolguev-Pechora Water near the southeastern ice edge. Cold water regions (Barents Sea Water, Arctic Water, Novaya Zemlya Coastal Water) exhibited low spring Chl-a concentrations (0.03–0.3 mg m−3). Generalized additive models identified hydrological variables (temperature and salinity), dissolved oxygen content, and nutrient concentrations (nitrite, nitrate, phosphate) as significant predictors explaining a substantial portion of the Chl-a variability.

Spatio-Temporal Variability of Algal Bloom in the Caspian Sea

Seasonal, interannual variability and spatial distribution of algal bloom in the North, Middle and South Caspian Sea has been investigated on the basis of Aqua MODIS chlorophyll-a (Chl-a) concentration data. Multi-year data demonstrate that over the two past decades Chl-a concentration has increased only in the North Caspian where the main rivers Volga and Ural enter the sea. In the Middle and South Caspian, it has shown weak negative linear trends. Special attention is paid to anomalous phytoplankton bloom, first of all cyanobacteria, in the South Caspian. Over 24 years of satellite observation, 1999-2022, abnormally intense phytoplankton bloom has been detected 8 times. Till present, it remains an open question what causes such outbreaks of intense algal bloom in the South Caspian. Generally, the literature and our studies suggest a variety of possible drivers of algal bloom, such as high sea surface and air temperature, low wind speed, high Chl-a concentration in periods preceding the development of phytoplankton bloom, atmospheric precipitation, and even dust storms. However, for the South Caspian we have found no clear correlation with any of these factors. Satellite monitoring of intense blooms, especially cyanobacteria, is of vital importance because cyanobacteria can produce potent toxins that can cause negative consequences for wildlife, ecosystems and even affect human health.

Research on the Inversion of Chlorophyll-a Concentration in the Hong Kong Coastal Area Based on Convolutional Neural Networks

Chlorophyll-a (Chl-a) concentration is a key indicator for assessing the eutrophication level in water bodies. However, accurately inverting Chl-a concentrations in optically complex coastal waters presents a significant challenge for traditional models. To address this, we employed Sentinel-2 MSI sensor data and leveraged the power of five machine learning models, including a convolutional neural network (CNN), to enhance the inversion process in the coastal waters near Hong Kong. The CNN model demonstrated superior performance with on-site data validation, outperforming the other four models (R2 = 0.810, RMSE = 1.165 μg/L, MRE = 35.578%). The CNN model was employed to estimate Chl-a concentrations from images captured over the study area in April and October 2022, resulting in the creation of a thematic map illustrating the spatial distribution of Chl-a levels. The map indicated high Chl-a concentrations in the northeast and southwest areas of Hong Kong Island and low Chl-a concentrations in the southeast facing the open sea. Analysis of patch size effects on CNN model accuracy indicated that 7 × 7 and 9 × 9 patches yielded the most optimal results across the tested sizes. Shapley additive explanations were employed to provide post-hoc interpretations for the best-performing CNN model, highlighting that features B6, B12, and B8 were the most important during the inversion process. This study can serve as a reference for developing machine learning models to invert water quality parameters.

Hydro-ecological modelling of a hypersaline lagoon ecosystem (Pulicat) in Southeast coast of India

Climate change impacts the coastal lagoons and can affect various species reproductive cycles, feeding habits, and survival. Due to natural factors, the ecosystem habitat at Pulicat Lagoon on the east coast of India is under severe stress. This study assesses the ecosystem using a numerical model and field-collected physical, chemical, biological, and meteorological data for 2018 and 2019. A coupled hydro-ecological model was used to analyze circulation features, biological and chemical interactions, and transformation processes. The study indicates that high abnormalities in the lagoon ecosystem are caused by less exchange of fresh/coastal water from river sources and sea mouths due to less rainfall during the study period. The model output depicts the salinity variation from 15 to 58 PSU in different seasons of 2018 and 2019. Furthermore, high concentrations of Chl-a ranged from 50 μg/L to 95 μg/L during the monsoon and post-monsoon seasons, triggering phytoplankton C (70–350 mg/m3) and zooplankton C (9–43 mg/m3) at the Lagoon, resulting in an algal bloom. The monsoonal shift of Chlorophyte (9.52%–9.68%), Cyanobacteria (13.22%–14.95%), Diatoms (66.08%–63.87%), and Dinoflagellates (11.18%–11.51%) is observed in the biological field, with Diatom showing the highest abundance (65%). As a result, appropriate scenario-based model studies were conducted to conserve and strengthen the ecosystem during such extreme events. The model studies suggest that widening the lagoon inlet (800m) with a depth of 5 m (3 km length) increases the optimal tidal exchange to the ecosystem. The model output demonstrates the optimal exchange that normalizes the salinity from 12 to 34 PSU from the inner Lagoon to the mouth region. This study will support environmental authorities in conserving the ecosystem through proper management adaptations.

Analysing Spatiotemporal Variability of Chlorophyll-a Concentration and Water Surface Temperature in Coastal Lagoons of the Ebro Delta (NW Mediterranean Sea, Spain)

Coastal lagoons are highly productive transitional water bodies threatened by human factors and vulnerable to global climate change effects. Monitoring biophysical parameters in these ecosystems is crucial for their preservation. In this work, we used Sentinel-2 and Landsat imagery combined with in situ data to (1) develop preliminary algorithms for retrieving the Chl-a concentration and water surface temperature of six lagoons located in the Ebro Delta (NE Mediterranean Sea, Spain), and to (2) compute maps and trend lines for analysing their spatiotemporal evolution from 2015 to 2022. Our findings showed that the algorithms’ accuracy ranged from 72% to 78% and had limited potential under high Chl-a concentration regimes. Even so, they revealed the lagoons’ trophic status, usual fluctuations, and deviations of both parameters attributed to seasonal (i.e., light and temperature) and short-term physical (i.e., winds) forcing, as well as valuable spatial patterns potentially useful for conservation efforts and land use planning. Future work will focus on the acquisition of a larger in situ data sample under a range of environmental conditions to improve the algorithms’ robustness, which in turn will allow the investigation of natural and human factors controlling the dynamics of the two investigated parameters.

Spatial distribution and environmental/biological co-regulation mechanism of dimethyl sulfur compounds in the eastern Indian Ocean

Dimethyl sulfur compounds including dimethylsulfoniopropionate (DMSP), dimethyl sulfide (DMS), and dimethyl sulfoxide (DMSO), play a crucial part in global sulfur cycling. The eastern Indian Ocean (EIO), characterized by its remarkable diversity of biomes and climate dynamics, is integral to global climate regulation. However, the regulation mechanism of DMS (P, O) in the EIO remains to be elucidated in detail. This paper presented a field survey aimed at investigating the spatial distribution of DMS (P, O) and their relationships with environmental and biological factors in the EIO. The surface concentrations of DMS, DMSPt, and DMSOt varied from 0.07 to 7.37 nmol/L, 0.14 to 9.17 nmol/L, and 0.15 to 3.32 nmol/L, respectively, and their distributions are attributed to high Chl-a concentration near Sri Lanka and the influence of ocean currents (Wyrtki jets, Bay of Bengal runoff). Higher concentrations of DMS (P) and DMSOt were predominantly observed in water columns shallower than 75m and deeper than 75m deep, respectively. The monthly DMS fluxes in the study area peaked in August. Temperature and Dissolved Silica Index (DSI) were the key environmental determinants for DMS distribution, while nitrate (NO3-) was the primary factor for both DMSPt and DMSOt. In terms of biological factors, Prochlorococcus and Synechococcus were significant contributors to DMS (P, O) dynamics. Synechococcus was the dominant influence on the DMS source and DMSPt sink, whereas Prochlorococcus primarily consumed DMSOt. Furthermore, the structural equation modeling (SEM) revealed the relationship between DMS, DMSPt, DMSOt, and the key environmental/biological factors, as well as among them, and together they formed a co-regulatory network in the EIO. This contributes significantly to the advancement of global ecosystem models for DMS (P, O).

Water and sediment chemistry drivers of chlorophyll-a dynamics within a Ramsar declared floodplain pan wetland system.

Floodplain pans are hydrologically dynamic in nature and characterised by variables such as chlorophyll-a (chl-a), water, and sediment chemistry over their hydroperiods. The present study investigated the spatio-temporal variations in water and sediment physico-chemical, and chlorophyll-a concentration characteristics of six floodplain pans found in the Ramsar declared Makuleke wetlands, Kruger National Park, South Africa. The water and sediment physico-chemical variable values were generally elevated during the high-water period, whereas chlorophyll-a concentrations varied across pans and hydroperiod. Benthic chl-a concentration significantly varied across pans with concentrations ranging from 161 to 1036.2mg m2. The two-way ANOVA showed significant differences in benthic chl-a concentration among hydroperiods, and no significant differences were observed in pelagic chl-a across pans and hydroperiods. Generally, pelagic and benthic chl-a concentration increased as water and sediment chemistry variables increased. Furthermore, three sediment variables, i.e. pH, calcium, and magnesium, and water conductivity were found to be significant in structuring benthic chlorophyll-a dynamics in pans. However, none of the sediment and water variables had a significant effect on pelagic chl-a. Hydroperiod had a significant effect on influencing chl-a concentration, with high and low water level periods being characterised by low and high chl-a concentration, respectively. The n-MDS results showed strong overlaps in chl-a biomass among the Makuleke floodplain pans across hydroperiods. The increasing chl-a concentration in these floodplain pans due to potential bioturbation effects as a result of large mammals could potentially lead to eutrophication, which in turn could affect the system's primary productivity and aquatic biota. Therefore, it is important to establish a continuous monitoring programme on these pans to inform sound management decisions.

Temporal and Spatial Distribution of Phytoplankton and Role of Environment Factors in the Shending River Backwater in the Danjiangkou Reservoir Area

The Danjiangkou Reservoir supplies drinking water to most residents in northern China. However, signs of eutrophication have been observed in the inlet tributaries of the reservoir, including the Shending River backwater. This research used data from the Sentinel-2 Multispectral instrument and findings from a 2021 aquatic ecological survey to analyze the spatial and temporal characteristics of phytoplankton distribution in the Shending River backwater region. The average chlorophyll a (Chl-a) concentrations by season, ranked from largest to smallest, are as follows: summer (63.96 μg/L) &gt; autumn (41.26 μg/L) &gt; spring (27.47 μg/L) &gt; winter (16.21 μg/L); the upstream of the backwater area and the near-shore tributary bay had relatively higher Chl-a concentration. Bacillariophyceae (Cyclotella meneghiniana and Synedra sp.) and Cryptophyceae species (Chroomonas acuta) were dominant in spring, whereas Chlorophyceae (Scenedesmus sp. and Chlorella vulgaris) and Cyanophyceae (Dactylococcopsis acicularis, Microcystis aeruginosa and Oscillatoria tenuis) species were dominant in summer. The seasonal succession characteristics of the phytoplankton community were consistent with those of the Plankton Ecology Group model. The average phytoplankton cell density was 4.80 × 107 cells/L, and the Shannon–Wiener average diversity index was 1.95, indicating that the Shending River backwater area was moderately eutrophic. According to Pearson correlation analysis and Mantel test, the main factors causing temporal and spatial differences in phytoplankton production in the Shending River’s backwater were water level (WL), water temperature (WT), ammonia nitrogen (NH3-N) and total nitrogen (TN). In particular, WL was significantly positively correlated with Bacillariophyceae, Chlorophyceae and Cyanophyceae, whereas WT was significantly correlated with Cryptophyceae and Chlorophyceae. NH3-N and TN were significantly correlated with Cyanophyceae. Therefore, intensive nitrogen removal from the tailwater of sewage treatment plants may be considered a feasible measure to prevent cyanobacterial bloom in the Shending River backwater of the Danjiangkou Reservoir.

Evaluation of Sentinel-2 Based Chlorophyll-a Estimation in a Small-Scale Reservoir: Assessing Accuracy and Availability

Small-scale reservoirs located in river estuaries are a significant water resource supporting agricultural and industrial activities; however, they face annual challenges of eutrophication and algal bloom occurrences due to excessive nutrient accumulation and watershed characteristics. Efficient management of algal blooms necessitates a comprehensive analysis of their spatiotemporal distribution characteristics. Therefore, this study aims to develop a chlorophyll-a (Chl-a) estimation model based on high-resolution satellite remote sensing data from Sentinel-2 multispectral sensors and multiple linear regression. The multiple linear regression (MLR) models were constructed using multiple reflectance-based variables that were collected over 2 years (2021–2022) in an estuarine reservoir. A total of 21 significant input variables were selected by backward elimination from the 2–4 band algorithms as employed in previous Chl-a estimation studies, along with the Sentinel-2 B1-B8A wavelength ratio. The developed algorithm exhibited a coefficient of determination of 0.65. Spatiotemporal variations in Chl-a concentration generated by the algorithm reflected the movement of high Chl-a concentration zones within the body of water. Through this analysis, it turned out that Sentinel-2-based spectral images were applicable to a small-scale reservoir which is relatively long and narrow, and the algorithm estimated changes in concentration levels over the seasons, revealing the dynamic nature of Chl-a distributions. The model developed in this study is expected to support effective algal bloom management and water quality improvement in a small-scale reservoir or similar complex water quality water bodies.

Terrestrial and Biological Activities Shaped the Fate of Dissolved Organic Nitrogen in a Subtropical River‐Dominated Estuary and Adjacent Coastal Area

AbstractEstuaries are key areas for terrestrial material transport and marine biogeochemical processes, particularly those of dissolved inorganic nitrogen (DIN) and dissolved organic nitrogen (DON). However, the fate of DON in estuaries with a high runoff remains poorly understood. In this study, we explored the translocation and transformation of DON in the Pearl River Estuary (PRE) and adjacent coastal areas of southern China based on DON concentrations, optical and fluorescence characteristics, and environmental parameters. The results revealed that DIN and DON exhibited dissimilar distributions. The distribution of DIN was primarily influenced by freshwater‐seawater mixing. In contrast, biological processes and freshwater‐seawater mixing shaped the distribution of DON. High levels of DON in the terrestrial‐dominated zone were predominantly anthropogenic sources through terrestrial inputs, whereas DON in the freshwater‐seawater mixing zone and seawater‐based zone were mainly influenced by biological activities, as high concentrations of Chla were observed in these two areas. DON exhibits fast dilution in low‐salinity areas and retention in moderate‐salinity areas (freshwater‐seawater mixing area) in summer and winter, while undergoes a rapid decrease in open water areas during winter. Consequently, DON in the PRE and adjacent coastal areas exhibited nonconservative mixing despite seasonal variations. These findings provide novel insights into the role of DON in nitrogen biogeochemical processes in river‐dominated estuaries and adjacent coastal areas.

Effects of Tropical Cyclone (TC) Hellen on the north-westward movement of chlorophyll in the northern Mozambique Channel.

An intense tropical cyclone (TC), TC Hellen, occurred in the northern Mozambique Channel on March 27, 2014, and moved from the east coast of the African continent to the northern Madagascar island. TC Hellen dramatically altered the marine environment in the northern Mozambique Channel, resulting in a significant chlorophyll-a (Chl-a) bloom. A giant surface Chl-a northwest-ward movement from the northwest coast of Madagascar Island was first observed after the passage of TC Hellen in the northern Mozambique Channel. The dynamic mechanisms of these phenomenon were studied by satellite remote sensing, multisource reanalysis data, and Argo float data. The results show that transient northwestward-moving eddies, upwelling, and winds had important effects on the Chl-a bloom and its northwestward movement. Ekman transport driven by coastal southeasterly winds entrained waters with high Chl-a concentrations to the northwest, while TC Hellen enhanced cyclonic eddy upwelling and uplifted nutrient-rich deep water to the upper ocean. This vertical mixing and upwelling in turn triggered the Chl-a bloom in the offshore surface layer. This study provides insight into the reflection of phytoplankton dynamics by TCs in the northern Mozambique Channel.

Seasonal and interannual variations of surface chlorophyll-a in the Karimata Strait

ABSTRACT This study aimed to evaluate the dynamics driving seasonal and interannual surface chlorophyll-a (chl-a) variability in the Karimata Strait (KS). The analysis shows that high chl-a concentrations were observed in the KS during December – February (northwest monsoon season) extending northwestward along the eastern coast of Peninsular Malaysia and northeastward along the northern coast of Borneo Island. This high chl-a concentration contrasts with the low chl-a concentration observed along the southern coast of Sumatra and Java during the same season. A substantial upwelling signal was identified in the central-eastern section of the South China Sea and along the northern coast of Java and the eastern coast of Sumatra from December to February. The positive wind stress curl forced downwelling in the southern section of the KS and the northern half of the Java Sea off the coast of Kalimantan. The elevated chl-a concentration in the KS during the northwest monsoon season could not be attributed to wind dynamics alone. The increase in surface chl-a concentration during the northwest monsoon season was associated with an increase in allochthonous nutrients from river discharges caused by increased precipitation over land. On an interannual timescale, a high chl-a concentration was observed during the southeast monsoon season when the La Niña event occurred in the tropical Pacific. The warm SST, associated with favourable downwelling winds, was observed over the entire the KS. It is suggested that anomalous chl-a that bloomed during the La Niña event was associated with anomalously high precipitation over land that transported nutrients to KS through river discharge.

Anomalous trend of chlorophyll-a as a response to mesoscale phenomena in a Brazilian oligotrophic ria

Saco do Mamanguá is a tropical Brazilian ria characterized by low nutrient availability and subject to seasonal thermocline, which is mainly influenced by the intrusion of South Atlantic Central Water (SACW) on the continental shelf. Sampling was performed in summer (2014, 2015) and spring (2017). The dissolved inorganic and organic nutrients (nitrogen [N] and phosphorus [P]), along with chlorophyll-a (Chl-a), were evaluated to characterize this area. As a result, the general trophic condition of Saco do Mamanguá is a meso-oligotrophic ria with low Chl-a concentrations. Due to the presence of an atmospheric phenomena that causes an extremely dry period during the summer of 2014, a strong thermocline was observed in the water column which was associated with high Chl-a concentrations (median of 6.14 mg m−3). These values were much higher than those observed during the summer of 2015 and in the spring of 2017 (median of 1.03 mg m−3). The dissolved inorganic nutrients presented low values in all studied periods with concentrations of nitrate (0.00–0.20 μmol L−1) and phosphate (0.00–0.20 μmol L−1). A wide range of dissolved organic compounds were also observed, as shown by the presence of dissolved organic carbon (DOC), which varied from 63 to 212 μmol L−1; dissolved organic nitrogen (DON), which varied from 2.97 to 12.92 μmol L−1; and dissolved organic phosphorus (DOP), which reached a maximum value of 0.63 μmol L−1. DON and DOP represented at least 50% total dissolved N and P. In this region, the biogeochemical cycles of N and P could ensure the availability of regenerated nutrients from organic sources to support primary production of phytoplankton.

Influence of resampling techniques on Bayesian network performance in predicting increased algal activity

Early warning of increased algal activity is important to mitigate potential impacts on aquatic life and human health. While many methods have been developed to predict increased algal activity, an ongoing issue is that severe algal blooms often occur with low frequency in water bodies. This results in imbalanced data sets available for model specification, leading to poor predictions of the frequency of increased algal activity. One approach to address this is to resample data sets of increased algal activity to increase the prevalence of higher than normal algal activity in calibration data and ultimately improve model predictions. This study aims to investigate the use of resampling techniques to address the imbalanced dataset and determine if such methods can improve the prediction of increased algal activity. Three techniques were investigated, Kmeans under-sampling (US_Kmeans), synthetic minority over-sampling technique (SMOTE), and ‘SMOTE and cluster-based under-sampling technique’ (SCUT). The resampling methods were applied to a Bayesian network (BN) model of Lake Burragorang in New South Wales, Australia. The model was developed to predict chlorophyll-a (chl-a) using a range of water quality parameters as predictors. The original data and each of the balanced datasets were used for BN structures and parameter learning. The results showed that the best graphical structure was obtained by adding synthetic data from SMOTE with the highest true positive rate (TPR) and area under the curve (AUC). When compared using a fixed graphical structure for the BN, all resampling techniques increased the ability of the BN to detect events with higher probability of increased algal activity. The resampling model results can also be used to better understand the most important influences on high chl-a concentrations and suggest future data collection and model development priorities.

Seasonal nutrients variation, eutrophication pattern, and Chlorophyll a response adjacent to Guangdong coastal water, China

Nutrients were the key biogenic elements for the primary production in coastal water, and the increase of nutrient concentration led to eutrophication and frequent occurrence of harmful algal blooms. However, the seasonal nutrients variation, eutrophication pattern, and Chlorophyll a (Chl-a) response adjacent to Guangdong coastal water were still scarcely. In this study, to clarity the seasonal nutrients variation, eutrophication pattern, and Chl-a, response adjacent to coastal water, the spatiotemporal dissolved inorganic nitrogen (DIN) and phosphorus (DIP) patterns and Chl-a were explored by field observation using 52 stations in the coastal waters of Guangdong Province during the dry (April and May), wet (July and August) and normal (October and November) seasons in 2020. The results showed that the variability of Chl-a, DIN and DIP were significantly different in seasons (P&amp;lt;0.01), and the mean concentrations of Chl-a, DIN and DIP were 11.97 ± 28.12 μg/L, 25.84 ± 35.72 μmol/L and 0.59 ± 0.71 μmol/L.Among them, the mean value of Chl-a increased significantly from 9.99 ± 9.84 μg/L in the dry season to 18.28 ± 38.07 μg/L in the wet season, and then decreased significantly to 7.65 ± 27.64 μg/L in the normal season.The mean DIN value decreased significantly from 30.68 ± 43.58 μmol/L in the dry season to 21.91 ± 35.45 μmol/L in the wet season, and then increased to 24.91 ± 26.12 μmol/L in the normal season. the mean DIP value decreased from 0.58 ± 0.73 μmol/L in the dry season to 0.48 ± 0.65 μmol/L in the wet season and then increased significantly to 0.70 ± 0.73μmol/L in the normal season. In addition, the DIN and DIP concentrations at most monitoring stations met the Grade II national seawater quality standards, and only a few monitoring stations fail to meet the Grade IV national seawater quality standard. The DIN/DIP ratios ranged from 2.05 to 259.47, with an average of 43.77 ± 41.01, far exceeding the Redfield ratio, indicating the presence of P limitation in the nearshore waters of Guangdong Province. Besides, the EI values in the coastal waters of Guangdong Province are higher at 0.00 and 82.51, with an average of 4.16 ± 10.90. DIN and DIP were significantly and positively correlated with COD in each season (P&amp;lt;0.05). Moreover, DIN/DIP showed significantly positive correlations with Chl-a in all seasons (P&amp;lt;0.01), indicating that high Chl-a concentrations could be sustained by the nutrients supply in marine ecosystems. Therefore, it is necessary to strengthen the integrated management of land and sea and effectively mitigate regional estuarine and coastal water eutrophication and harmful algal blooms.

Remote sensing-based spatiotemporal variation and driving factor assessment of chlorophyll-a concentrations in China’s Pearl River Estuary

Climate change and intensive anthropogenic activities have severely challenged the water quality of China’s Pearl River Estuary (PRE). Further investigations into long-term water quality variation and associated driving mechanisms are therefore necessary to support the sustainable development of the PRE’s Greater Bay Area (GBA). This study used remote sensing retrieval to address long-term spatiotemporal chlorophyll-a (Chl-a) variation characteristics in the PRE and the relationship between Chl-a concentrations and socioeconomic/environmental indicators. Three decades of Landsat satellite images and measured data were collected, and a two-band global algorithm was used to retrieve Chl-a concentration data. Results reveal significant spatiotemporal variability in Chl-a concentrations. The space-averaged Chl-a concentration exhibited a slight downward trend during the past three decades, and the multi-year mean value was 5.20 mg/L. Changes to environmental protection policies in recent years have improved overall PRE water quality. The western section of the PRE had the highest Chl-a concentration (i.e., 5.92 mg/L average) while the eastern section had the lowest (i.e., 3.98 mg/L average). This discrepancy was likely caused by the western section’s more intensive industrial activities, resulting in a higher overall wastewater discharge volume. Affected by climatic conditions, winter Chl-a concentrations were evenly distributed while summer concentrations were significantly higher. Additionally, Chl-a concentrations significantly and positively correlated with total phosphorus (TP), total nitrogen (TN), ammonia nitrogen (NH3-N), and the biotic oxygen demand (BOD5). Chl-a concentrations also correlated with external factors (i.e., climate and anthropogenic activities). Among these factors, industrial wastewater discharge and the proportion of primary industries in coastal cities significantly and positively correlated with water quality. This study is intended to help direct water quality improvement management and urban sustainable development in the GBA.

Seasonal and spatial variability in bio-optical properties of the Persian Gulf: Implications for ocean color remote sensing

In this study, the absorption coefficients of phytoplankton community (aPh(λ)), Colored Dissolved Organic Matter (CDOM) [aCDOM(λ)], and Non-Algal Particles (NAP) [aNap(λ)] were analyzed in the northern Persian Gulf, a Mediterranean-type semi-enclosed marginal sea, through seven cruise expeditions conducted from May 2018 to February 2022. The highest and lowest aPh(443) values were observed in the shallow area (depth ≤20 m) during the wet season (November–April) (0.043 ± 0.004 m-1) and within the deep area (depth >20 m) through the dry season (July–September) (0.024 ± 0.003 m-1), respectively. The chlorophyll-specific absorption (a*Ph(λ)) values increased from the deep to shallow areas as well as the wet to dry seasons. A significant difference was further detected in a*Ph(λ) magnitude at the blue (443 nm) and red (675 nm) wavelengths, with the mean values of 0.0124/0.0223 m2 mg−1 and 0.0069/0.0135 m2 mg−1 in the wet/dry seasons, respectively. The mean values of aCDOM(443) in the shallow area during the wet season (0.10 ± 0.001 m-1) were significantly larger than those in the deep area during the dry season (0.06 ± 0.002 m-1). Similarly, aNAP(443) decreased from the shallow (0.056 ± 0.021 m-1) to deep areas (0.019 ± 0.011 m-1), and from the wet (0.035 ± 0.020 m-1) to dry (0.029 ± 0.015 m-1) seasons. The statistical analysis revealed that the differences in aCDOM(λ) and aNAP(λ) spectral distribution were not statistically significant for the duration of the wet and dry seasons, whereas significant differences were observed in the shallow and deep samples. During both wet and dry seasons, the magnitude of the blue-green absorption spectra was dominated by CDOM, but the red bands were associated with phytoplankton dominated samples. The ratio of aCDOM(λ)/a*Ph(λ) was utilized as an index for uncertainty assessment to estimate Chl-a concentrations by the National Aeronautics and Space Administration (NASA) standard Chl-a algorithms for the Moderate Resolution Imaging Spectrometer (MODIS; OC3M) and Sentinel-3 Ocean and Land Color Instrument (OLCI) (OLCI; OC4v6). The results additionally demonstrated that the satellite-derived Chl-a was overestimated due to higher aCDOM(λ) and underestimated owing to lower a*Ph(λ) at the low (<0.5 mg m−3) and high (>3 mg m−3) concentrations of Chl-a, respectively. The study findings established that the red bands should be considered for tuning or developing new Chl-a algorithms in the Persian Gulf.