Water Trophic Status Research Articles

Relative impact of environmental variables on the lake trophic state highlights the complexity of eutrophication controls

For the effective management of lakes apart from defining and monitoring their current state it is crucial to identify environmental variables that are mostly responsible for the nutrient input. We used interpretative machine learning to investigate the environmental parameters that influence the lake's trophic state and recognize their patterns. We analysed the influence of the 25 environmental variables on the commonly used trophic state indicators values: total phosphorus (TP), Chlorophyll-a (Chl-a) and Secchi depth (SD) of 60 lakes located in the Central European Lowlands. We attempted to delineate the lakes into groups due to the influence of common prevailing environment variable/variables on the water trophic state reflected by each indicator. The results indicated that the relative impact of environmental variables on the lake trophic state has an individual hierarchy unique for each indicator. The most important are variables related to catchment impact on the lake, Ohle ratio (L. catchment area/L. area) for TP and Schindler ratio (L. area + L. catchment area)/L. volume for Chl-a and SD. There are also few variables strongly influential only for small sub-groups of lakes that stand out: lake maximum depth, catchment slope steepness expressed by the height standard deviation. The methods used in the study enabled the assessment of the character of the influence of the environmental variables on the indicator value and revealed that most essential variables (Ohle ratio for TP and Schindler ratio for Chl-a and SD) have bimodal distribution with a clear threshold value. These findings contribute to a better understanding of the drivers shaping the lake trophic status and have implication for planning effective management strategies.

IMPROVING THE WASTE WATER QUALITY OF CATFISH FARMING POND THROUGH PHYTOREMEDIATION PROCESS BATCH CULTURE SYSTEM USING VARIOUS TYPES OF LOCAL HYDROMACROPHYTES

This study aimed to determine the effectiveness of the batch culture phytoremediation model conducted in a 30 L bucket with sand and gravel as a substrate in reducing pollutants from post-harvest catfish farming ponds. This true experimental study used a completely randomised design with the treatments of hydromacrophytes of emergent, floating, submerged, and polycultures of the three hydromacrophytes and controls without hydromacrophytes. Each treatment was repeated three times. The effectiveness of this model was monitored using physicochemical water parameters, Chironomidae density, and the biotic index of diatom [Trophic Diatom Index (TDI) and Percentage of Pollution Tolerant Value (%PTV)]. After incubation, monitoring was done on days 10, 15, 20, and 25. The results showed that the phytoremediation process had successfully reduced the suspended solid and nitrate levels in the water starting from day ten after incubation. The levels of Biochemical Oxygen Demand (BOD) and Total Kjeldahl Nitrogen (TKN) decreased significantly after 25 days. The level of organic matter pollution based on the %PTV and density of Chironomidae was significantly reduced after 15 days of incubation. However, the phosphate level was still high, and the water trophic status was hypereutrophic. The most effective treatment for the phytoremediation process in this study is submerged hydromacrophytes.

Zooplankton community dynamics in response to water trophic state in integrated multitrophic aquaculture

Integrated multitrophic aquaculture (IMTA) is an alternative means to optimize feed usage in aquaculture which combines species of different trophic levels. The addition of substrate to IMTA has also been used to promote a lower release of phosphorus, thus minimizing eutrophication and impacts of effluents. In these aquaculture systems, the zooplankton community is important because it acts as a link in trophic chains. This study aimed to verify the dynamics and the structure of the zooplankton community in IMTA (tilapia-prawn), in response to trophic conditions in earthen ponds with different substrates. The object of the study was 12 earthen ponds organized in three treatments: no substrate (control), geotextile substrate, and bamboo substrate. Zooplankton samples were taken biweekly through a water bilge pump. Rotifers and microcrustaceans were identified and counted to determine changes in community diversity during the experiment. Eutrophication was determined through phosphorus and chlorophyll water concentrations. There were no differences in zooplankton communities among treatments, even though increases in levels of eutrophication of the system heavily influenced this community, by altering its diversity and abundance. Small organisms were the most representative ones under polyculture eutrophic conditions.

Spatiotemporal Variability of the Lake Tana Water Quality Derived from the MODIS-Based Forel–Ule Index: The Roles of Hydrometeorological and Surface Processes

Lake Tana, the largest inland water body in Ethiopia, has witnessed significant changes due to ongoing urbanization and socioeconomic activities in recent times. In this study, the two-decade recordings of moderate resolution imaging spectroradiometer (MODIS) were used to derive Forel–Ule index (FUI). The FUI, which ranges from 1 (dark-blue pristine water) to 21 (yellowish-brown polluted water), is important to fully understand the quality and trophic state of the lake in the last two decades. The analysis of FUI over a period of 22 years (2000–2021) indicates that Lake Tana is in a eutrophic state as confirmed by FUI values ranging from 11 to 17. This is in agreement with the trophic state index (TSI) estimated from MERIS diversity-II chlorophyll a (Chl_a) measurements for the overlapping 2003-2011 period. The categorical skill scores show that FUI-based lake water trophic state classification relative to MERIS-based TSI has a high performance. FUI has a positive correlation with TSI, (Chl_a), turbidity, and total suspended matter (TSM) and negative relations with Chl_a and TSM (at the lake shoreline) and colored dissolved organic matter. The annual, interannual and seasonal spatial distribution of FUI over the lake show a marked variation. The hydro-meteorological, land-use–land-cover (LULC) related processes are found to modulate the spatiotemporal variability of water quality within the range of lower and upper extremes of the eutrophic state as revealed from the FUI composite analysis. The FUI composites were obtained for the terciles and extreme percentiles of variables representing hydro-meteorological and LULC processes. High FUI composite (poor water quality) is associated with above-normal and extremely high (85 percentile) lake bottom layer temperature, wind speed, precipitation, surface runoff, and hydrometeorological drought as captured by high negative standardized precipitation-evapotranspiration index (SPEI). In contrast, a high FUI composite is observed during below-normal and extremely low (15 percentile) lake skin temperature and evaporation. Conversely good water quality (i.e., low FUI) was observed during times of below-normal and above-normal values of the above two sets of drivers respectively. Moreover, FUI varies in response to seasonal NDVI/EVI variabilities. The relationship between water quality and its drivers is consistent with the expected physical processes under different ranges of the drivers. High wind speed, for instance, displaces algae blooms to the shoreline whereas intense precipitation and increased runoff lead to high sediment loads. Increasing lake skin temperature increases evaporation, thereby decreasing water volume and increasing insoluble nutrients, while the increasing lake bottom layer temperature increases microbial activity, thereby enhancing the phosphorus load. Moreover, during drought events, the low inflow and high temperature allow algal bloom, Chl_a, and suspended particles to increase, whereas high vegetation leads to an increase in the non-point sources of total phosphorus and nitrogen.

Can IMTA provide added ecosystem value services in the fish farms of Greece?

In addition to food supply, there is a growing recognition of the wider ecosystem benefits of Integrated Multitrophic Aquaculture (IMTA) systems in coastal waters, including regulating services such as carbon sequestration and nutrient remediation. The water trophic status and the co-cultured species combinations affect IMTA productivity. In this study, we examined the ability of different combinations of IMTA organisms to remediate nutrients and the economic/environmental gain for reducing the environmental footprint in potential IMTA systems of the eastern Mediterranean. The results showed that the co-cultivation of organisms can reduce the negative effects on the marine environment of a fish farm both on the water column and the sediment. Meso- and eutrophic water states do not show a high variation in terms of foot print mitigation, with all three of the co-cultivated organisms to perform well. In oligotrophic waters, the obligatory absence of mussels reduces the effectiveness of the IMTA system. As expected, larger-sized IMTA systems have higher production rates and as a result higher percentage of nutrient removal. Finally, bivalve harvesting helps to remove the carbon that is trapped in their shells, contributing to the mitigation of processes related to climate change, such as the acidification of the oceans.

Freshwater trophic status mediates microbial community assembly and interdomain network complexity

Freshwater microorganisms and their interactions are important drivers of nutrient cycling that are in turn affected by nutrient status, causing shifts in microbial community diversity, composition, and interactions. However, the impact of water trophic status on bacterial-archaeal interdomain interactions remains poorly understood. This study focused on the impact of trophic status, as characterized by trophic state index (TSI), on the interdomain interactions of freshwater microbial communities from 45 ponds in Hangzhou. Our results showed that the mesotrophic wetland bordering on lightly eutrophic (Hemu: TSI of 49; lightly eutrophic is defined as 50 ≤ TSI <60) harbored a much more complex bacterial-archaeal interdomain network, which showed significantly (P < 0.05) higher connectivity than the wetlands with lower (TSI of 38) or higher (TSI of 57) trophic levels. Notably, light eutrophication strengthened the network modules’ negative associations with organic carbon through some network hubs, which could trigger carbon loss in wetlands. We also detected a non-linear response of interdomain network complexity to the increasing of nutrients with a turning point of approximately TSI 50. Quantitative estimates of community assembly processes and structural equation modelling analysis indicated that chlorophyll-a, total nitrogen, and total phosphorus could regulate interdomain network complexity (50% of the variation explanation rate) by driving microbial community assembly. This study demonstrates that microbial interdomain network complexity could be used as a bioindicator for ecological changes, which would helpful for improving ecological assessment of the freshwater eutrophication.

The universal trophic index: new methodological approach to eutrophication monitoring and control

Anthropogenic eutrophication is one of the consequences of human activities observed from the beginning of urbanization processes and is now a widespread problem around the globe. Mitigation of eutrophication directly corresponds to the achievement of at least three main Sustainable Development Goals. Due to the complexity of eutrophication mechanisms, there are still many issues with managing this process and its consequences, that complicate the achievement of the above-mentioned objectives. So far, there is no universal definition of eutrophication and there is no unified methodological approach to surface water trophic status assessment. In connection with the above, a need arises for the development of scientifically and economically justified methods of reliable trophic state assessment, useful for solving application and engineering tasks. This paper presents a new approach to trophic state assessment based on the innovative universal trophic index (UTI), which can be used for fresh, brackish and saltwater bodies. The proposed UTI index was developed and verified using an extensive database of the Baltic Sea monitoring data for over 100 years. The elaborated method is a reliable tool for the assessment of water trophic status, which also allows for the development of predictive mathematical models as the basis for effective eutrophication management. In addition, the method is simple to use and enables the trophic state assessment at low cost, time and effort. The above-mentioned features make the proposed indicator meet the requirements set for modern ecological indicators and determine the advantage of the proposed methodological approach over other currently used methods.

Improving remote sensing retrieval of global ocean transparency with optical water classification

• Remote sensing empirical inversion expressions of ocean water transparency (Z sd ) for different optical water types and water trophic states. • A class-based hybrid Z sd empirical model for global oceans. • Long-term spatiotemporal climatology patterns of global ocean Z sd . Ocean water transparency is an important indicator to measure the productivity of marine ecosystems, and it has great impact on phytoplankton biomass and community structure. Secchi disk depth (Z sd ) is a traditional measure of water transparency. With the development of satellite remote sensing technology, inversion through empirical model or semi-analytical model has become an effective and efficient means to obtain ocean Z sd . In recent years, ocean parameter inversions based on water classification become an ongoing trend. Jia et al. (2021) constructed a fuzzy-logic optical water type scheme (i.e., U-OWT) for the global oceans and multi satellite sensors, which was a potential water classification template for remote sensing inversion of ocean Z sd . Using U-OWT as the water classification basis, and by collecting 613 global ocean distributed SeaWiFS (Sea-viewing Wide Field-of-view Sensor) R rs and Z sd (with the range of 0.3–44.3 m) in-situ matchups, this study explored the optimal Z sd empirical models for each optical water type and each water trophic state respectively. As a result, a class-based Z sd hybrid empirical model (abbreviated as the Z sd-OWT model) was developed, which had relative high inversion accuracy over the entire Z sd range (MAPE = 8.25 %, RMSE = 0.65 m, bias = – 0.03 m). Specifically, the Z sd-OWT model conducted the global empirical inversion for the oligotrophic water classes and the class-based hard fusion empirical inversions for the mesotrophic and the eutrophic water classes. Although the Z sd-OWT model was designed for SeaWiFS sensor, it still has the potential to be migrated to other multispectral sensors with similar band settings.

Inland Water Trophic State Identification using Remote Sensing data and Machine Learning Approach

Providing information on inland waters’ trophic state levels (oligotrophic, mesotrophic, eutrophic, and hypereutrophic) is considered more effective in communicating the lake’s conditions to the public and policymakers than water quality. It is highly demanding for a straightforward method to estimate inland waters’ trophic state. This study proposes a model for estimating the lake trophic state levels from remote sensing data. We used simulation data to overcome data limitations in building the classification model. The simulation data consists of one nanometer (nm) interval spectra, paired with calculated Secchi Disk Depth (SD in m) representing various water types. We convert the spectra into Landsat band configuration and classify SD into four trophic state levels. We compare four machine learning classification models, i.e., Classification and Regression Trees (CART), k-Nearest Neighbour (k-NN), Support Vector Machine (SVM), Random Forest (RF), and select the best model using the Kappa Index. We apply the selected model to satellite images and estimate trophic state levels of various lakes across time and space. Our result demonstrated that the developed model could robustly identify the lake trophic state levels. This rapid identification procedure could provide valuable spatial and temporal information of the lake’s conditions for the public and policymakers to support inland water sustainable management.

STRUCTURAL CHANGES OF RIVER ECOSYSTEMS’ BIOLOGICAL QUALITY ELEMENTS UNDER CONDITIONS OF MINERAL WATER FLUX

The Government of the Republic of Armenia strives to ensure a better management of surface water resources by establishing regular hydrobiological monitoring system in accordance with the EU WFD requirements. However, there is a very limited use of biological quality elements in monitoring of the ecological status of surface waters due in part to a lack of studies on their reflection towards different stressors. Thus, the aim of the study was to estimate the structural changes of benthic macroinvertebrates and macrophytes under the influence of the mineral water flux. The hyperlocal studies have been conducted in the area where the single stressor is mineral water. The results have shown that benthic macro invertebrates are more sensitive towards mineral water flux than macrophytes which allowed also to conclude on the higher efficiency of use of macrophytes in the estimation of water trophic status in case of mixed effects of organic pollution and mineral waters.

Water quality and trophic status of Lake Mariut in Egypt and its drainage water after 8-year diversion

Water resource management and lake rehabilitation are global interest, to overcome the acute water scarcity facing most urban areas, especially in developing countries. Lake Mariut (LM) is an Egyptian lake that lies south of the Mediterranean Sea, and its management had a great interest in Alexandria’s future development and as a part of the environmental sustainability of the Mediterranean basin. LM consists of 4 major basins, namely, main (MB), northwest (NWB), southwest (SWB), and fishery (FB). The MB has deteriorated as it consistently received (sewage and industrial) wastewaters till 2010. This was the date of diversion of the polluting sources as a rehabilitation step. The present work is made after elapsing 8 years from the diversion and aims at monitoring and assessing the status of the water quality not only of MB but also for the other 3 basins too. This was carried out twice, one in cold winter and the other in warm summer. The parameters studied were physico-chemical including water temperature, pH, dissolved oxygen/hydrogen sulfide (DO/H2S), salinity, and chlorophyll a besides nutrient salts (nitrogen, N and phosphorus, P compounds). The results revealed that the waters of both MB and SWB basins were depleted in DO to a level difficult to sustain fish life and showed elevated levels of most nutrient salts. Trophically, all the studied basins were in eutrophic-hypereutrophic condition. As a result of pollution source diversion away from MB to be discharged in the downstream part of Umum Drain (UD), the levels of TN and TP entering Mex Bay through UD were slightly higher than the permissible limit and lower than dangerous loading. The applying of principle component analysis (PCA)-based classification approach, for obtaining the WQI on the current study, revealed that the FB, NWB, and SWB2000 showed a relatively good water quality when compared with MB. The depletion in the vital DO is catastrophic and needs urgent solution/s. One of the proposed solutions is the dredging of bottom spoiled organic-rich sediments. This and other suggested solutions are, however, discussed, evaluated, and presented.

Water Quality and Trophic Status of Lake Toba, North Sumatra, Indonesia

Water Quality and Trophic Status of Lake Toba, North Sumatra, Indonesia

Development of a Periphytic Diatom-Based Comprehensive Diatom Index for Assessing the Trophic Status of Lakes in the Lower Reaches of the Yangtze River, China

Periphytic diatoms play important functional roles in aquatic ecosystems. Their community compositions are widely used in water quality monitoring due to their wide distribution, short reproductive cycles, and sensitivity to environmental changes. In this study, 116 samples of periphytic diatom samples were collected from lakes in the lower reaches of the Yangtze River. The weighted average without tolerance down-weighting regression method was used to develop total phosphorus (r2 = 0.661), total nitrogen (r2 = 0.699), and chemical oxygen demand (r2 = 0.423) models, and the optimal and tolerance values of 78 periphytic species were calculated. Then, a new index, the comprehensive diatom index (CDI), was established on the basis of the optima and tolerances of these 78 species concerning the three environmental variables (TP, TN, and COD) to assess the water trophic status of the lakes in this region. According to the CDI, the trophic statuses of 8, 17, 23, 30, 22, and 14 sample sites were oligotrophic, mesotrophic, light eutrophication, moderate eutrophication, heavy eutrophication, and ultra-eutrophication, respectively. The CDI was more strongly correlated with the conductivity, pH, TP, TN, COD, and TDS than other diatom indices. These results demonstrate that the CDI is a useful metric for assessing the water trophic status of the lakes in the lower reaches of the Yangtze River.

Analysis of Factors Influencing the Trophic State of Drinking Water Reservoirs in Taiwan

Eutrophication is an environmental pollution problem that occurs in natural water bodies. Regression analyses with interaction terms are carried out to identify the factors influencing the Shimen, Mingde, and Fongshan Reservoirs in Taiwan. The results indicate that the main factor influencing these reservoirs is total phosphorus. In the Shimen and Mingde Reservoirs, the influence of total phosphorus, when interacting with other factors, on water quality trophic state is more serious than that of total phosphorus per se. This implies that the actual influence of total phosphorus on the eutrophic condition could be underestimated. Furthermore, there was no deterministic causality between climate and water quality variables. In addition, time lagged effects, or the influence of their interaction with other variables, were considered separately in this study to further determine the actual relationships between water trophic state and influencing factors. The influencing patterns for three reservoirs are different, because the type, size, and background environment of each reservoir are different. This is as expected, since it is difficult to predict eutrophication in reservoirs with a universal index or equation. However, the multiple linear regression model used in this study could be a suitable quick-to-use, case-by-case model option for this problem.

A unified model for high resolution mapping of global lake (>1 ha) clarity using Landsat imagery data

Lake clarity, usually measured by Secchi disc depth (SDD), is a reliable proxy of lakes trophic status due to its close link with total suspended matter, chlorophyll-a, and nutrients. Trained with in-situ measured SDD and match-up Landsat images, we established various regression models to estimate SDD for global lakes. We selected a unified model which demonstrated good spatiotemporal transferability, and has potential to map SDD in different years with good quality of Landsat top-of-atmosphere (TOA) images embedded in Google Earth Engine (GEE). The unified model was successfully calibrated (n = 3586 data points, R2 = 0.84, MAPE = 29.8%) against SDD measured in 2235 lakes across the world, and the validation (n = 1779, R2 = 0.76, MAPE = 38.8%) also exhibited stable performance. The unified model was tuned to historical SDD measurements coincident with different Landsat sensors (L5-TM, L7-ETM+, L8-OLI) launched over the past four decades (1984–2020), thus confirming its temporal stability. Global SDD was mapped using GEE with OLI TOA products mainly acquired in 2019 to examine the spatial variation of lake water clarity (lake surface area ≥ 1 ha) all over the world. Worldwide, lake water clarity averaged 3.13 ± 1.71 m in 2019, but exhibited remarkable spatial variability due to catchment hydrological and landscape settings, lake morphology, elevation and anthropogenic impact. Inland waters in Europe (4.18 ± 1.82 m) and North America (3.84 ± 1.77 m) had the highest clarity due to greater water depth combined with less human disturbance in the high latitude regions. Lakes in South America (2.50 ± 2.33 m), Asia (2.44 ± 1.63 m) and Africa (2.36 ± 0.72 m) displayed intermediate clarity. Lakes in Oceania (1.97 ± 1.48 m) exhibited the lowest clarity for all continents except Antarctica. Further, we used the mapped SDD to evaluate water trophic status using the Carlson trophic state index. Our results indicate that, in 2019, about 63.6% of the lake areas and 47.8% of total lake numbers (2,219,627/4,646,056) were oligotrophic for global lakes, while about 23.6% areal percent and 37.1% of lake numbers are eutrophic mostly as a result of their being located in agricultural and urban-dominated drainage basins. This study, for the first time, provides water clarity information for lakes with area ≥ 1 ha all over the world with 30-m resolution and facilitates the understanding of the water clarity relevant to TSM (r = 0.95), Chl-a (r = 0.73), total phosphorus (r = 0.75), total nitrogen (r = 0.60), which could further provide water clarity data and technical support for trophic level evaluations as well. This unified model could serve as a powerful research tool for long-term monitoring of aquatic ecosystems and assessing their resilience to anthropogenic disturbance and climate change-related stressors.

Spatial distribution of nutrients in Maumere Bay, East Nusa Tenggara

The availability of nutrients in the marine environment is very important for primary production and as indicator of the health condition in waters. East Nusa Tenggara Province is one of the province that has a potential fishery, especially in Maumere Bay of Sikka Regency. Therefore, it is necessary to monitor the water quality and spatial distribution of nutrients in that area. This study aims to determine water quality, assess water trophic status, and determine limiting factors in Maumere Bay. Sampling was conducted in August 2017 at 14 research stations and 1 daily station. The results showed that the relationship between DIN, DIP, and DSi at the daily station was a weak correlation. DIN reaches maximum concentration after 8 hours, whereas DIP and DSi reach maximum concentration after 12 hours. The average DIN, DIP, and DSi were 1.082 μmol L−1, 0.123 μmol L−1, and 4.544 μmol L−1, respectively. The average DIN/DIP ratio was 11.554. It can be concluded that Maumere Bay is an oligotrophic area and phosphate as a limiting nutrient for phytoplankton growth.

Influence of Seascape on Coastal Lagoon Fisheries: the Role of Habitat Mosaic in the Venice Lagoon

Fisheries are a staple human activity supported by coastal lagoons. Together with water quality and trophic status, lagoon morphology is acknowledged as one of the main ecological drivers of fishery yields; however, the role of lagoon seascape structure is still poorly understood. This paper investigates how morphological variables, habitat distribution and seascape diversity and complexity affect yields of artisanal fishery performed with fyke nets in the Venice Lagoon (northern Adriatic Sea, Italy). Two spatial scales were considered in the analysis, with water quality parameters (temperature, salinity, dissolved oxygen, turbidity, water residence times, N, P and chlorophyll-a concentrations) being measured at a fine, fyke-net scale and morphological (average bottom elevation and sediment grain size) and habitat features (habitat proportion, diversity and complexity) being measured at a broader, seascape scale. Generalised linear mixed models were employed to model 8 years of nekton and green crab catches, disentangling the role of broad-scale morphology and seascape from that of fine-scale water quality. Broad-scale variables clearly influenced fishery target species. Among them, lagoon residents were associated with specific morphological and habitat characteristics, while marine migrants showed a stronger link with overall habitat diversity and complexity. This evidence emphasises how artisanal fishery in the Venice Lagoon relies on the conservation of morphological and habitat heterogeneity. Moreover, it highlights how habitat restoration performed at the seascape level should also be taken into account, in addition to controlling hydrology and water quality, when managing fishery resources in coastal lagoons.

Assessing trophic status of Suoi Hai Reservoir using Carlson’s Trophic State Index

The water quality of Suoi Hai reservoir, the largest reservoir in Hanoi city, is being threatened by human activities of the surrounding area, as reported by the press. The trophic status of the reservoir is the result of both natural eutrophication and nutrient inputs from anthropogenic sources, particularly the leachate from a lakeside waste treatment plant. This study aims to identify the trophic status of the Suoi Hai reservoir and the changes of water trophic state over space and time. Data of chlorophyll-a concentration, total phosphorus, and Secchi disk depth from 51 sites during three field campaigns in October 2019, August 2020, and March 2021 was used to calculate Carlson’s trophic state index (CTSI). Resultant CTSI (ranged from 60 to 72) allows classifying Suoi Hai reservoir as highly eutrophic water. Its variations in space and time provided evidence for an influence of anthropogenic activities on the reservoir trophic state. Analysis of the trophic state index deviations suggested that total phosphorus is the key factor that influenced the reservoir trophic state. Therefore, managing the anthropogenic nutrient inputs load to the reservoir should be a critical task to control eutrophication in Suoi Hai Reservoir at present.

Assessment of Trophic Responses of a Reservoir to Seasonal and Annual Variations in Monsoon

The variations in water quality parameters and trophic status of a multipurpose reservoir in response to changing intensity of monsoon rain was investigated by applying a trophic state index deviation (TSID) analysis and an empirical regression model to the data collected in two periods from 2014 to 2017. The reservoir in general maintained mesotrophic conditions, and Carlson’s trophic state index (TSIc) was affected most by TSITP. Nutrient concentrations, particularly phosphorus, did not show strong correlations with precipitation, particularly in the period with weak monsoon, and a significant increase in total phosphorus (TP) was observed in Spring 2015, indicating the possibility of internal phosphorus loading under decreased depth and stability of water body due to a lack of precipitation. TSIChl was higher than TSISD in most data in period 1 when a negligible increase in precipitation was observed in the monsoon season while a significant fraction in period 2 showed the opposite trend. Phytoplankton growth was not limited by nutrient limitation although nutrient ratios (N/P) of most samples were significantly higher than 20, indicating phosphorus-limited condition. TSID and regression analysis indicated that phytoplankton growth was limited by zooplankton grazing in the Spring, and that cell concentrations and community structure in the monsoon and post-monsoon season were controlled by the changing intensity of the monsoon, as evidenced by the positive and negative relationships between community size and cyanobacterial population with the amount of precipitation in the Summer, respectively. The possibility of contribution from internal loading and an increase in cyanobacterial population associated with weak monsoon, in addition to potential for nutrient enrichment in the post-monsoon season, implies a need for the application of more stringent water quality management in the reservoir that can handle all potential scenarios of eutrophication.

A Machine Learning Approach for Estimating the Trophic State of Urban Waters Based on Remote Sensing and Environmental Factors

To improve the accuracy of remotely sensed estimates of the trophic state index (TSI) of inland urban water bodies, key environmental factors (water temperature and wind field) were considered during the modelling process. Such environmental factors can be easily measured and display a strong correlation with TSI. Then, a backpropagation neural network (BP-NN) was applied to develop the TSI estimation model using remote sensing and environmental factors. The model was trained and validated using the TSI quantified by five water trophic indicators obtained for the period between 2018 and 2019, and then we selected the most appropriate combination of input variables according to the performance of the BP-NN. Our results demonstrate that the optimal performance can be obtained by combining the water temperature and single-band reflection values of Sentinel-2 satellite imagery as input variables (R2 = 0.922, RMSE = 3.256, MAPE = 2.494%, and classification accuracy rate = 86.364%). Finally, the spatial and temporal distribution of the aquatic trophic state over four months with different trophic levels was mapped in Gongqingcheng City using the TSI estimation model. In general, the predictive maps based on our proposed model show significant seasonal changes and spatial characteristics in the water trophic state, indicating the possibility of performing cost-effective, RS-based TSI estimation studies on complex urban water bodies elsewhere.