Hyper-Nutrient Enrichment Status in the Sabalan Lake, Iran

Satellite-Based Monitoring of Eutrophication in the Earth's Largest Transboundary Lake

The world's large lakes and their life-supporting services are rapidly threatened by eutrophication in the warming climate during the Anthropocene. Here, MODIS-Aqua level 3 chlorophyll-a data (2018-2021) were used to monitor trophic state in our planet's largest lake, that is, the Caspian Sea that accounts for approximately 40% of the total lacustrine waters on Earth. We also used the in situ measurements of chlorophyll-a data (2009-2019) to further verify the accuracy of the data derived from the MODIS-Aqua and to explore the deep chlorophyll-a maxima (DCMs) in the south Caspian Sea. Our findings show an acceptable agreement between the chlorophyll-a data derived from the MODIS-Aqua and those measured in situ in the coast of Iran (coefficient of determination = 0.71). The oligotrophic, mesotrophic, and eutrophic states cover 66%, 20%, and 13% of the sea surface area, respectively. The DCMs are dominantly regulated by water transparency and they generally observe at depths of less than 20 and 30 m during the cold (autumn and winter) and warm (spring and summer) seasons, respectively. Our results suggest an ever-increasing chlorophyll-a in the shallow zones (i.e., coasts) and even in deep regions of the sea, mainly due to nutrient inputs from the Volga river delta. Alarming increase of chlorophyll-a in this transboundary lake can amplify eutrophication under the lens of global warming and further threaten the lake ecosystem's health, where almost all legal agreements have not yet been implemented to protect the lake environment and its rich resources.

Modelling impacts of climate change and anthropogenic activities on inflows and sediment loads of wetlands: case study of the Anzali wetland

Understanding the effects of climate change and anthropogenic activities on the hydrogeomorpholgical parameters in wetlands ecosystems is vital for designing effective environmental protection and control protocols for these natural capitals. This study develops methodological approach to model the streamflow and sediment inputs to wetlands under the combined effects of climate and land use / land cover (LULC) changes using the Soil and Water Assessment Tool (SWAT). The precipitation and temperature data from General Circulation Models (GCMs) for different Shared Socio-economic Pathway (SSP) scenarios (i.e., SSP1-2.6, SSP2-4.5, and SSP5-8.5) are downscaled and bias-corrected with Euclidean distance method and quantile delta mapping (QDM) for the case of the Anzali wetland watershed (AWW) in Iran. The Land Change Modeler (LCM) is adopted to project the future LULC at the AWW. The results indicate that the precipitation and air temperature across the AWW will decrease and increase, respectively, under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. Streamflow and sediment loads will reduce under the sole influence of SSP2-4.5 and SSP5-8.5 climate scenarios. An increase in sediment load and inflow was observed under the combined effects of climate and LULC changes, this is mainly due to the projected increased deforestation and urbanization across the AWW. The findings suggest that the densely vegetated regions, mainly located in the zones with steep slope, significantly prevents large sediment load and high streamflow input to the AWW. Under the combined effects of the climate and LULC changes, by 2100, the projected total sediment input to the wetland will reach 22.66, 20.83, and 19.93 million tons under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios, respectively. The results highlight that without any robust environmental interventions, the large sediment inputs will significantly degrade the Anzali wetland ecosystem and partly-fill the wetland basin, resulting in resigning the wetland from the Montreux record list and the Ramsar Convention on Wetlands of International Importance.

A sediment diagenesis model on sediment oxygen demand in managing eutrophication on Taihu, China

Blue-green algae (CyanoHABs), photosynthetic bacteria that create a harmful aquatic environment, have been a trending issue on Taihu for over a decade. CyanoHABs adapt to varying climatic changes, which explains why the problem on Taihu still thrives. One major drive that keeps the algae is Sediment Oxygen Demand (SOD). In this paper, seasonal and spatial variations of SOD that contribute immensely to nutrient growth in Lake Taihu were done using the Environmental Fluid Dynamics Code (EFDC). The results were analyzed based on Nitrogenous SOD (NSOD) and Total SOD (TSOD). Summer results ranged from - 0.05754 to - 0.0826 (- 0.75658 to - 0.83902) (g/m²/day) and Winter values ranged from - 0.3022 to - 0.40171 (- 1.34486 to - 1.48856) (g/m²/day) indicate a gradual decrease in NSOD (TSOD) values respectively. Relatively higher values in summer are attributed to warmer surface water which sets up thermal stratification to increase the internal loading of nitrogen. Lower winter values are related to inverse stratification, where lower oxygen concentration decreases the SOD to trigger ammonium accumulation in the water column. NSOD (TSOD) values for Autumn results ranged from - 0.1039 to - 0.24786 (- 0.96251 to - 1.39454) (g/m²/day) and Spring values of - 0.43019 to - 0.35959 (- 1.48297 to - 0.54089) (g/m²/day). Transition seasons (i.e., Autumn and Spring) results are impacted by wind mixing that allows dissolved oxygen and nutrients in the whole water column. However, spring values depict a gradual increase in SOD value attributed to spring turnover and gradual stratification, which decrease nutrient concentration. In contrast, decreasing SOD values in autumn are related to mixing, but temperature decreases tend to increase nutrient concentrations. Carbonaceous sediment oxygen demand (CSOD), due to sulfide oxidation, presents high values from the difference between TSOD and NSOD. Based on the high values of CSOD, it is highly recommended that more research on eutrophic Taihu lakes would consider delving into CSOD.

Linking river flow modification with wetland hydrological instability, habitat condition, and ecological responses

Flow modification pursuing dams is widely found. Some works also focused on its impact on floodplain wetland hydrology. However, how this change can pose an impact on habitat conditions, ecological conditions, and trophic state is also a matter of investigation. The very least attention has been paid to this so far. Therefore, the present study focused on these, taking the dam-induced Lower Tangon river basin of India and Bangladesh as a case. The degree of flow alteration in the river was presented in a heat map. Multi-parametric machine learning (ML) approaches were applied to model hydrological instability and habitat condition. The ecological consequences like evaluating eco-deficit using flow duration curve (FDC) approach, trophic state using trophic state index (TSI), fish habitat zone using image-based hydrological parameters, etc. were measured. The study exhibited that after damming, the degree of river flow modification was about 41%. Consequently, the wetland hydrological instability and habitat conditions were degraded. In the post-dam period, > 50% of wetland area was lost, and hydrological instability was enhanced considerably over wider parts of the wetland. Habitat conditions of the existing wetland also witnessed fragility (poor and very poor areas increased by about 22.23 and 9.34%). As a result of this, adverse ecological responses were found. For instance, the eco-deficit area was increased by 36.19%, a good proportion (100%) of wetlands was witnessed the transformation of TSI from oligotrophic to mesotrophic state, and optimum fish habitat area was declined. The ecological strength map integrating all the cause-effect model parameters showed that good ecological strength was reduced from 49 to 2% in the post-dam. The result of the study would be very useful for wetland restoration for ecological and human well-being.

Hydrogeochemical characterization based water resources vulnerability assessment in India's first Ramsar site of Chilka lake

A limnological site is significantly characterized by rich biological, chemical, and physical properties of the environment and is also described as the epitome of a large aquatic ecosystem. During the last few decades, the Chilka lake Ramsar site has experienced substantial degradation of water quality with associated deterioration of aquatic biodiversity. Our study aims to quantify the VWRM of the Chilka lake Ramsar region using the most reliable MLAs, namely ANN and RF, with the help of seventeen hydro-chemical properties of lake water. The produced map is validated through six validating measures (ROC-AUC- 0.89, Sensitivity-0.90, Specificity-0.78, PPV-0.78, NPV-0.88, Taylor diagram (r)-0.94), which depict that ANN is the most reliable ML algorithm in assessing the VWRM of the concerned region followed by RF. The prepared map of our study revealed that the eastern part was remarkably high to very high vulnerable zone covered area with 22.41 % and 7.19 %, respectively.

Internal phosphorus loading and its driving factors in the dry period of Brazilian semiarid reservoirs

This study investigated the relationships between physical, limnological and climatic drivers with the internal total phosphorus (TP) loading produced over the dry period in 30 water supply reservoirs of the Brazilian semiarid. Improvements in the understanding of sedimentary TP fluxes in reservoirs of dryland regions are pressing as they usually have serious water quality related issues, remaining mostly eutrophic especially under frequent drought events. Gross daily fluxes and net seasonal average release rates were calculated from mass balance and regression equations considering water and sediment TP concentrations, anoxic duration, water temperature and fish contribution. Additionally, the ratio of wind speed to reservoir volume was proposed as a new surrogate and then applied as explanatory variable to predictive models. The results indicated TP release rates higher than reported for non-semiarid lakes/reservoirs with average gross fluxes ranging from 17.64 to 35.99 mg m^-2 day^-1. This may be attributed to the enriched sediments (1029.49 ± 552.49 mg kg^-1) allied with warmer water temperature, high trophic state, and prolonged anoxic periods (average duration of about 60 days). The average release rates were negatively correlated with water transparency and water depth, and positively correlated with Chl-a, wind speed and trophic state. The release rates increased across the trophic gradient (p < 0.05), about 10-fold higher under hypertrophic conditions than in oligotrophic ones. As anoxia is linked with eutrophication, phosphorus release is more likely in eutrophic ecosystems. Regarding the new surrogate, a strong predictive ability for TP release (R²: 0.26-0.93) was observed. Similarly, the proposed models presented a physically consistent behavior with a stabilizing releasing pattern suggesting the achievement of equilibrium in nutrient exchange between sediment-water interface. This research advanced by combining and proposing methods to assess and quantify sedimentary fluxes in data-scarce regions balancing accuracy and transferability, in order to be replicable to other dryland environments globally.

Spatiotemporal Distribution Pattern of Phytoplankton Community and Its Main Driving Factors in Dongting Lake, China—A Seasonal Study from 2017 to 2019

As it is the second-largest freshwater lake downstream of the Three Gorges Dam and an important international wetland for migratory birds, there have been concerns about the ecological water health of Dongting Lake for a long time. In the present study, we studied the evolutionary characteristics of water quality in Dongting Lake in three recent years. Moreover, the evolution rules and dominant groups of the phytoplankton community were explored, and the major influencing factors of phytoplankton and their distribution were assessed based on the field survey and detection data from 2017 to 2019. The results indicated that the water quality of Dongting Lake improved in recent years. The concentration of dissolved oxygen (DO) increased by 6.91%, whereas the concentrations of the five-day biochemical oxygen demand (BOD5), chemical oxygen demand (CODCr), ammonia nitrogen (NH4+–N), total phosphorus (TP), and total nitrogen (TN) decreased by 17.5%, 13.0%, 33.8%, 7.6%, and 13.3%, respectively. The mean phytoplankton density reached 4.15 × 105 cells·L−1 in September 2017, whereas it was only 1.62 × 105 cells·L−1 in December 2018. There were 15 dominant species belonging to Cyanobacteria, Chlorophyta, Bacillariophyta, Cryptophyta, and Miozoa. Moreover, Fragilaria radians (Kützing) D.M.Williams & Round and Aulacoseiragranulata (Ehrenberg) Simonsen were the dominant populations in all seasons. The Pearson and linear regression analysis also indicated that the composition and distribution of phytoplankton in Dongting Lake were mainly affected by electrical conductivity (Cond), BOD5, potassium permanganate (CODMn), and CODCr, especially in Eastern Dongting Lake. Of course, NH4+–N, TN, and TP were also the main factors affecting the density and species of the phytoplankton community, especially in Western Dongting Lake. Finally, we suggested that local government could take “The relationship between Yangtze River and Dongting Lake”, “The relationship between the seven fed rivers and Dongting Lake”, and “The relationship between human activities and Dongting Lake” as the breakthrough points to guarantee the ecological flow, water environment, and ecological quality of Dongting Lake.

Hydrodynamic Drivers of Nutrient and Phytoplankton Dynamics in a Subtropical Reservoir

Chlorophyll-a (chla) is an important parameter to assess water quality in lakes and reservoirs, since it is a proxy for phytoplankton biomass and primary production. The increasing availability of data with high spatial and temporal resolution allows assessing short-term dynamics and small-scale variations of chla within larger water bodies. In freshwater reservoirs, the nutrient concentrations and the physical conditions that control phytoplankton growth vary along their longitudinal extend. Here, we analyze how the flow paths of the inflowing river water into density-stratified reservoirs affect the vertical and longitudinal distribution of nutrients and chla. We combine spatially resolved and high-frequency measurements of chla from satellite remote sensing and in-situ sensors, with numerical simulations using a three-dimensional hydrodynamic model to assess the influence of density currents on chla dynamics along a subtropical drinking water reservoir in the south of Brazil. Chla did not have pronounced seasonal dynamics (4.9 ± 1.2 µg L−1, at the continuous measurement station); instead, spatial variability along the reservoir was more pronounced (4.4 ± 2.1 µg L−1, all monitored points within the euphotic zone). Most of the nutrients from the inflowing river were consumed in the upstream region, and phytoplankton in the lacustrine zone depended on internal loading. Temporal variability was observed only in the upstream region, and phytoplankton produced in that area was transported downstream by density currents, resulting in large concentrations of chla below the euphotic zone. The results of a hydrodynamic model that simulates the present state are in good agreement with the observations. Two simulated scenarios, where the density current patterns were altered, resulted only in slight variations in density currents, indicating that the influence of the main inflow was of minor relevance in chla concentrations in downstream regions of the reservoir. Our results highlight the importance of two-dimensional hydrodynamic processes in regulating phytoplankton dynamics in reservoirs.

Construction and Application of a Water Quality Risk Sensitive Area Identification System in the Wudongde Reservoir

Numerous water quality risks exist during the initial water storage stage in reservoirs; however, little water quality data is available for this stage. Taking the Wudongde Reservoir as an example, we proposed a water quality risk sensitive area identification system for the initial impoundment stage comprising three modules: water quality assessment, water quality similarity clustering analysis, and sensitive area identification. Temporal and spatial variation in the water quality of the whole reservoir was analyzed, combined with a comprehensive evaluation using the Canadian Council of Ministers of the Environment Water Quality Index. A water quality similar clustering module was used to form similar clusters for monitoring sections in the reservoir area. The water quality risk sensitive areas were then identified and verified through a prototype test. The reservoir water quality was primarily excellent to good, although that of the Madian and Longchuan Rivers was poor. Through cluster analysis, the Madian River and tributaries of the Longchuan River were identified as sensitive areas, and the causes of water quality risk were analyzed. Based on these findings, we suggested focus areas for water environmental protection measures, providing a basis for the protection and restoration of the reservoir water environment.

Pollution and Release Characteristics of Nitrogen, Phosphorus and Organic Carbon in Pond Sediments in a Typical Polder Area of the Lake Taihu Basin

There is currently a lack of knowledge on the release characteristics of nutrients from artificial pond sediments in polder areas, resulting in problems in future management of such environments, including converting polders to lakes. In this study, sediment samples were taken from a fish pond and a lotus pond in a typical polder area of the Lake Taihu Basin in China. The total nitrogen (TN, 1760–1810 mg/kg), total phosphorus (TP, 1370–1463 mg/kg) and total organic carbon (TOC, 10.1–21.2 g/kg) contents were significantly higher than those found in sediments from the adjacent aquatic system, which indicates that the legacy of agricultural activities has had an obvious cumulative effect on pond sediment nutrients. The release behavior of TN, TP and TOC varied significantly, not only under disturbed and static conditions, but also from sediments sampled at different ponds and depths. During the disturbing condition, there were continuous releases of carbon and nutrients in the lotus pond sediments, while the fish pond sediments showed a higher release at the beginning. Under static release conditions, the release of TP in the surface and bottom sediments of the fish pond increased first, then decreased and stabilized within 24 h, while the release of the lotus pond showed a slow upward trend. Despite the lower concentration of nutrients and TOC, the lotus pond sediment showed a higher release rate. The results suggested that it is necessary to adopt different strategies for different types of ponds in the project of returning polders to lakes; it is especially important to pay attention to the release of nutrients from the bottom sediments of lotus ponds in the project management.

Long-Term Series of Chlorophyll-a Concentration in Brazilian Semiarid Lakes from Modis Imagery

By monitoring the chlorophyll a concentration (chla), it is possible to keep track of the eutrophication status of a lake and to describe the temporal dynamics of the phytoplankton biomass. Such monitoring must be both extensive and intensive to account for the short- and long-term biomass variations. This may be achieved by the remote estimation of chla through an orbital sensor with high temporal resolution. In this study, we used MODIS imagery to produce 21-year time series of chla for three strategic lakes of the Brazilian semi-arid region: Eng. Armando Ribeiro Gonçalves, Castanhão, and Orós. We used data collected in 13 lakes of the region to test new and published regression models for chla estimation. The selected model was validated and applied to daily MODIS images for the three largest lakes. The resulting chla time series revealed that the temporal dynamics of the phytoplankton biomass is associated with the hydraulic regime of the lakes, with chla plummeting upon intense water renewal and keeping high during persistent dry periods. The intense rainy season of 2004 reduced the phytoplankton biomass and its effects even extended to the subsequent years. Our results encourage the exploration of the MODIS archived imagery in limnological studies.

Assessment of Water Quality in Lake Qaroun Using Ground-Based Remote Sensing Data and Artificial Neural Networks

Monitoring and managing water quality parameters (WQPs) in water bodies (e.g., lakes) on a large scale using sampling-point techniques is tedious, laborious, and not highly representative. Hyperspectral and data-driven technology have provided a potentially valuable tool for the precise measurement of WQPs. Therefore, the objective of this work was to integrate WQPs, derived spectral reflectance indices (published spectral reflectance indices (PSRIs)), newly two-band spectral reflectance indices (NSRIs-2b) and newly three-band spectral indices (NSRIs-3b), and artificial neural networks (ANNs) for estimating WQPs in Lake Qaroun. Shipboard cruises were conducted to collect surface water samples at 16 different sites throughout Lake Qaroun throughout a two-year study (2018 and 2019). Different WQPs, such as total nitrogen (TN), ammonium (NH4+), orthophosphate (PO43−), and chemical oxygen demand (COD), were evaluated for aquatic use. The results showed that the highest determination coefficients were recorded with the NSRIs-3b, followed by the NSRIs-2b, and then followed by the PSRIs, which produced lower R2 with all tested WQPs. The majority of NSRIs-3bs demonstrated strong significant relationships with three WQPs (TN, NH4+, and PO43−) with (R2 = 0.70 to 0.77), and a moderate relationship with COD (R2 = 0.52 to 0.64). The SRIs integrated with ANNs would be an efficient tool for estimating the investigated four WQPs in both calibration and validation datasets with acceptable accuracy. For examples, the five features of the SRIs involved in this model are of great significance for predicting TN. Its outputs showed high R2 values of 0.92 and 0.84 for calibration and validation, respectively. The ANN-PO43−VI-17 was the highest accuracy model for predicting PO43− with R2 = 0.98 and 0.89 for calibration and validation, respectively. In conclusion, this research study demonstrated that NSRIs-3b, alongside a combined approach of ANNs models and SRIs, would be an effective tool for assessing WQPs of Lake Qaroun.