Lake Water Quality Assessment Research Articles

Urban transformation of lakes and its impacts on a lake series: A case study of the yele mallappa shetty lake series Bengaluru, India.

The interconnected systems of lakes of Bengaluru, India, experience tremendous stress due to unsustainable urbanisation. Traditional lake-centric research approach struggles to capture and address this issue due to the cascaded nature of impacts in interconnected lake systems. Hence, this study assesses the impact of urbanisation on a lake series scale, focusing on the Yele Mallappa Shetty Lake series (YMSLS). Land use land cover change analysis (1993-2023) showed that in 1993, the YMSLS catchment area was dominated by open spaces (53.4%) and agriculture land and vegetation (35%), with built-up areas covering only 7.2%. By 2023, the built-up area has expanded to 34.6% and became the dominant land use. This rapid urbanisation has led to increased water surface area from wastewater influx, causing significant weed growth and water pollution in the lakes. Lake water quality assessment showed that faecal coliform, total coliform, dissolved oxygen, and biochemical oxygen demand levels exceeded standard limits with spatio-temporal variations driven by interconnectivity. Pollutant flushing during monsoon reduced pollution load in upstream lakes, but high wastewater inflow made downstream lakes, particularly the end lake, highly polluted but perennial. Increased water availability expanded the user base of the end lake, but traditional uses have declined and coping strategies of users, such as wastewater lift irrigation from the lake, became unsustainable. The study indicates that spatial interdependence and cascading effects necessitate a lake series approach for assessing the impacts of urbanisation on interconnected lake system, which is crucial for enhancing water security and preparedness for future extreme events.

Solar powered integrated multi sensors to monitor inland lake water quality using statistical data fusion technique with Kalman filter

This study proposes a data-driven statistical model using multi sensor fusion and Kalman filtering for real-time water quality assessment in lakes. A recursive estimation technique, the Kalman Filter, is employed to handle uncertainties and enhance computational efficiency. The fusion process integrates data from sensors monitoring parameters like chlorophyll concentration, surface water elevation, temperature, and precipitation, producing Markov features to capture temporal transitions and environmental dynamics. Data synchronization and fusion are achieved through recursive KF methods, enabling real-time adaptive management in response to environmental fluctuations such as seasonal changes, precipitation (6–18%), and evaporation rates (1.2–11.9 mm/day). Over a 30-day evaluation period, the model accurately predicted chlorophyll concentrations, reaching 128 mg/m3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {mg}/\\hbox {m}^{3}$$\\end{document} in mid-level inflow regions (3.6 m water elevation) compared to 86 mg/m3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {mg}/\\hbox {m}^{3}$$\\end{document} in extreme inflow areas (5.5 m). The integration of Markov feature extraction and eigenvalue estimation enhanced prediction stability and sensitivity, with the KF maintaining computational efficiency at 7.8 ms per computation cycle. The model’s accuracy was validated by achieving a residual error of less than 0.05 with minimal noise interference. Overall, the system provides a resilient and precise framework for real-time lake water quality assessment, capable of handling multi-parameter uncertainties and dynamic environmental changes, thereby supporting informed decision-making for aquatic ecosystem management.

Lake Water Quality Assessment Through GIS based Interpolation Method: A Case Study of Beris Dam, Kedah, Malaysia

Preliminary research on physicochemical and water quality in the Beris dam shows that the water catchment area has the best standards and quality during the observation of the wet season and dry season mainly in the northern states of peninsular Malaysia. The analysis of water quality assessment using the DOE-WQI and Carlson Trophic State Index (CTSI) resulted that during the dry season (February), the average DOE-WQI reading is 88 or Class II; while during the wet season, the average DOE-WQI reading recorded 87.1 (October). Although the CTSI score was 34.2 - 27.0 during wet season and dry season, both seasons were classified as oligotrophic conditions. Some physicochemical parameters also show a high correlation between them and indicates minor water quality issues. The use of more efficient interpolation techniques in water quality studies also reinforces the evaluation of water quality. As a reference point for future water research, GIS interpolation application methods can be more effectively and efficiently used with Inverse Distance Weighted (IDW), Ordinary Kriging and Spline techniques. HIGHLIGHTS Investigation of physicochemical and water quality in lake water in Beris Dam Assessment by using water quality index by DOE-WQI and Carlson Trophic State Index (CTSI) to acknowledge water quality and trophic condition. Analyzing physicochemical data into mathematical method to compare between physicochemical data and correlate between them. Application of GIS based interpolation methods to analyze and referencing physicochemical data into spatial interpolation maps. Comparing appropriate spatial interpolation techniques to analyze physicochemical observation data and index. GRAPHICAL ABSTRACT

Lake Water Quality Assessment Based on Multispectral Unmanned Aerial Vehicle Images and In-Situ Testing

In recent years, Universiti Tun Hussein Onn Malaysia has experienced several developments in buildings and road construction. A stormwater retention pond was built as a part of the construction plan to prevent the occurrence of floods downstream of the development sites. However, poor monitoring and maintenance of the pond caused water contamination, which had bad effects on the nearby environment and lake ecosystem. Therefore, this study was conducted to assess the current water quality in the pond by using a combination between Multispectral Unmanned Aerial Vehicle images and in-situ sampling. Four water quality parameters were investigated, namely turbidity, dissolved oxygen, temperature, and pH. Aerial images were taken using a multispectral aerial mapping camera attached to UAV. The in-situ testing was performed on the same day of image capturing at 5 different locations. According to the results, it was found that the pH and water temperature were within the normal levels with maximum and minimum values of 7.34 and 6.94 for pH and 28.39oC and 28.04oC for temperature, respectively. Turbidity readings appaired with a significant variation with a maximum value of 30.9 NTU at the lake outlet and a minimum value of 18.8 NTU at the middle of the lake. Dissolved oxygen concentration was noticed to be low, with an average value of 4.3 mg/l. Water quality mapping showed the concentration distribution of each water quality parameter along the lake surface. In each map, the differences in terms of colours were found to be not significant because of the size of the lake, which is relatively small, as well as because of the small differences in terms of water quality ridings at each sampling point.

Current state of bacterioplankton of Lake Ilmen

Objective: Determination of the quantitative level of the Lake Ilmen bacterial community in a retrospective. Assessment of lake water quality by microbiological indicators based on the results of seasonal microbiological studies in 2022Research material and methods used: The material was samples of bacterioplankton from the surface water layer of the Lake Ilmen, collected in May, August and September 2022. The total numbers of microorganisms was determined by the epifluorescence method using DAPI fluorochrome. Standard methods were used to determine the number of saprophytic microorganisms at two temperature regimes.Originality: For the first time in the last 25 years, the quantitative characteristics of the bacterial community of Lake Ilmen were determined. A quality assessment of lake waters has been carried out, and the values of self-purification coefficients were calculated.Results: The microbiological characteristic of the water masses of Lake Ilmen, as a habitat for bioresources, is presented. The maximum values of the total bacterial numbers (TBN) were observed in May (average 5.05±0.52×106 cells/ml) during the spring flood, the minimum — at the end of September (average 3.21±0.89×106 cells/ml) during the cooling period of the lake. Coccoid cells prevailed in the bacterioplankton, which indirectly indicates the absence of contamination of the lake waters with organic matter of various origins. According to the average for the observation period TBN (4.10±1.05×106 cells/ml), the trophic state of the lake corresponded to weakly eutrophic. The number of saprophytic bacteria growing at 22 °С always exceeded that at 37oC, which indicated active self-purification processes. According to the quantitative ratios of the TBN and the number of saprophytic bacteria growing at 22 °С (OMH 22 °С), the water masses of the lake, with rare exceptions, belonged to the conditional category of “pure” (oligosaprobic)

Lake water quality assessment using spatial interpolation and the development of the WQI on an educational campus, Assam, India

Abstract Monitoring water quality metrics is essential for managing water quality and safeguarding aquatic life. The NIT Silchar Lake has been a place for many aquatic plants and migratory birds. The lake water is typically used on campus for horticultureal purposes. However, the peasants living close to campus use the lake water for drinking during situations like floods or famine. At four separate locations of the lake, the samples were collected for evaluation of seven water quality indicators. Temperature between 22.4 and 30.5 °C and dissolved oxygen concentrations between 8 and 13 mg/l were found, which were optimal conditions for aquatic life. The water quality index (WQI), which gives an overall evaluation of the state of the water quality, was created from the measured values (six parameters). The lake regions that ranged from good to excellent were identified using ‘weighted arithmetic water quality index’ (WAWQI) technique. Further we have compared the WAWQI with another method. A comparative analysis has been done by developing simple codes with the help of python programming language. The inverse distance weighted (IDW) interpolation in GIS was applied for spatial distribution of water quality parameters and WQI.

A spatiotemporal monitoring model of TSM and TDS in arid region lakes utilizing Sentinel-2 imagery

The assessment of lake water quality is crucial for protecting and managing natural resources. Total suspended matter (TSM) and total dissolved solids (TDS) are significant parameters in evaluating lake water quality, and their concentration levels provide useful information about the health of the ecosystem. However, measuring TSM and TDS concentrations in remote arid areas can be challenging, necessitating the development of a simple, efficient, and cost-effective monitoring system. In this study, the aim was to retrieve TDS and TSM concentrations in the arid region using an empirical and physics-based method simultaneously. Measured data and remote sensing images for Chah-Nimeh Reservoirs (CNRs), Iran, were used to establish the TSM and TDS concentration model. Twenty-seven Sentinel-2 multispectral instrument (MSI) data acquired from 2018 to 2021 were employed to determine the spatiotemporal distribution of TDS and TSM concentrations. The results indicate that Sentinel-2 MSI data is a productive tool for retrieving TSM concentration using the Case-2 Regional/Coastal Color (C2RCC) processor, with a high level of performance in the dry ecosystem of CNRs (R2 = 0.92). Furthermore, the Bayesian regularization artificial neural network (BRANN) algorithm was used to evaluate TDS concentration, and the results demonstrated that the BRANN algorithm outperforms other models, with a high level of performance (R2 = 0.89). It is noteworthy that evaluating TDS concentration is generally more challenging than TSM. The study provides a valuable model for monitoring TSM and TDS concentrations in remote arid areas using Sentinel-2 MSI data. The proposed approach can facilitate effective spatiotemporal monitoring of TSM and TDS concentrations and aid in the evaluation of lake water quality, specifically in regions where in-situ measurements are not feasible. The findings have significant implications for the management and conservation of natural resources in arid and remote regions.

Advancing potential of diatom indicators for stream and lake water quality assessment against nutrient-induced pollution

Advancing potential of diatom indicators for stream and lake water quality assessment against nutrient-induced pollution

Water Environmental Characteristics and Water Quality Assessment of Lakes in Tibetan Plateau

Lakes are an important water resource and biological habitat in the Tibetan Plateau. Owing to the combined influence of climate, topography, and other natural factors as well as human factors, the water environment of the lakes on the Tibetan Plateau is facing more and more severe problems and challenges. To clarify the present status, distribution pattern, main characteristic factors of water quality, and important factors affecting the water quality of lakes on the Tibetan Plateau, the water environment of 12 typical lakes on the Tibet Plateau was investigated in summer (July-August) and autumn (October-November) in 2020. The field sampling and laboratory test data comprehensive analysis showed that:① several physical and chemical parameters of typical lakes on the Tibetan Plateau differed in spatiotemporal distribution. ② Salinity was the main characteristic of water quality in the typical lakes on the Tibetan Plateau. ③ The spatiotemporal distribution of lake eutrophication index showed little diversity and basically ranged from poor nutrition to moderate nutrition. The spatial and temporal distributions in the lake water quality index (WQI) were significantly different. The lake WQI grade decreased from "Moderate" to "Very poor" with the increase in salinity area, and the lake water quality in autumn was better than that in summer. ④ The spatiotemporal differences in lake water quality on the Tibetan Plateau were mainly controlled by precipitation, evapoconcentration, and human activities. This study will provide scientific basis for water environment protection and improvement of water ecosystems on the Tibetan Plateau.

Water Quality Assessment of Lakes (Ain Al-Ghazala and Umm-Hufayn) for Fish Culture in the Eastern Coast of Libya

Assessments of some physical and chemical properties were conducted for two Libyan water bodies (Ain Al- Ghazala and Umm-Hufayn). Of each ecosystem, ten water samples were taken from ten points for analysis. The results showed that the electric conductivity in Ain Al-Ghazala Bay waters is higher than that in the waters of Umm-Hufayn Lake. In the two areas, the hydrogen ion concentration pH recorded the highest value with a value of 8.3, with mean values of chloride (Cl) exceeding the internationally recorded limits. Furthermore, nitrites (NO2), nitrate (NO3), sulphate (SO4), phosphate (PO4), silicates (SiO2), carbonate (CO3), calcium (Ca), magnesium (Mg), sodium (Na), and potassium (K) were all greater in Ain Al-Ghazala Bay waters than in Umm-Hufayn Lake waters. In conclusion, more attention should be directed to the preservation of such natural resources.

Sediment phosphate release flux under hydraulic disturbances in the shallow lake of Chaohu, China.

Quantifying the effect of hydraulic disturbances on sediment phosphate release is a key issue in the water quality assessment of lakes, especially for the shallow lakes which are susceptible to winds and waves. Here, we sampled the original sediment columns from 12 positions in the eastern, central, and western areas of the Chaohu Lake, a representative shallow lake in China, and observed phosphate release under three levels of hydraulic disturbances in the laboratory. When the disturbance was weak and sediment on the surface of bottom mud moved individually (the Individual Motion Mode), sediment phosphate release rate was insignificant (0.24mg/m2/day). When the disturbance was medium and only a small percentage (< 16%) of surface sediment started to move (the Small Motion Mode), the phosphate release rate sharply increased to 4.81mg/m2/day. When the disturbance was further strengthened and most (≥ 16%) of the surface sediment moved (the General Motion Mode), the phosphate release rate was more than doubled (10.23mg/m2/day). With the increase in hydraulic disturbance intensity, the variation range of phosphate release also became wider. Spatial distribution showed that the release rate varies the most in the western area, followed by the eastern and the central areas. By extrapolating the experimental results to the real scale, it was found that the phosphate release fluxes would probably fall within a wide range between 203.43 to 7311.01kg/day under different levels of hydrodynamic disturbances which considerably affects phosphate release from shallow lakes. This study also has implications for the pollutant management in other shallow lakes.

Chemical speciation of selected toxic metals and multivariate statistical techniques used to assess water quality of tropical Mexican Lake Chapala.

Mexican Lake Chapala is used as water supply for human consumption. Consequently, water quality of this lake is of paramount importance for the lake's wellbeing. The contribution presented in this paper investigates monitoring and assessment of lake water quality using water quality index (WQI), metal chemical speciation, and multivariate statistical techniques. Descriptive statistics shows total metal concentrations undetected conferring the lake a healthy status. Dissolved Cd and Pb exceed criterion continuous concentration limit, whereas Zn is below this limit indicating that water quality is satisfactory for aquatic life. However, WQI indicates poor water quality attributed to failure of conductivity, total solids, nitrogen, and phosphates, due to industrial and agro-industrial effluents. Metal speciations indicate that the presence of low concentrations of dissolved metals reflect interactions with gills of fish through metal-biotic ligand complexes affecting water quality. Positive correlations are obtained between conductivity and nitrates, indicating that agricultural activities and fertilizer runoffs increase the conductivity and that the environmental state of lake is being altered by human activities. Factors F1 (31%), F2 (19%), and F3 (11%) represent 61% of variability; F1 and F2 corroborate the pressure exerted by pollutants related with fertilizers and agrochemicals; F3 contains Zn and Pb with positive loads attributed to influx of tourist visitors. Sites S4, S5, S6, and S9 are identified as the most environmentally affected by COD, Alk*, pH, Cl-, nitrites, phosphates, and TS. Multivariate techniques permit to conclude that environmental stress of Lake Chapala is caused by variables pertaining to agrochemical, fertilizers and municipal wastes.

Assessment of lake water quality using multivariate statistical techniques and chlorophyll-nutrient relationships: a case study of the Göksu Lake

This study aimed to evaluate the water quality of the Goksu Lake, which is located in Ankara, Turkey. For this purpose, multivariate statistical analyses, namely, principal component analysis/factor analysis, regression analysis and cluster analysis, and linear regression analysis, were used to determine the relationship between the nutrients. In order to evaluate the status of the lake water quality, the limiting nutrient element was determined using the total nitrogen to total phosphorus ratio (TN/TP). The water quality parameters were selected as pH, turbidity, chemical oxygen demand (COD), suspended solids (SS), dissolved oxygen (DO), biochemical oxygen demand (BOD), total nitrogen (TN), chlorophyll-a (Chl-a), total phosphorus (TP), color, fecal coliform (FC), and total coliform (TC) count. For the cluster analysis, the single-link clustering method using Euclidean distance criteria was preferred. Cluster I consisted of sites 1, 2, 3, and 4, while cluster II consisted of site 5. Two factors were obtained as a result of the factor analysis. These two factors explained 88.2% of the total variance. The first factor clarifies the 45.62% of total variance has pH, COD, DO, TN, TP, color, BOD, and TC strong positive load value. This factor was thought to represent domestic wastewater. The second factor that affects water quality clarifies the 42.54% of total variance has turbidity, SS, Chl-a, and FC strong positive load value. This factor was thought to represent the microbiological activities that occurred as a result of the mixing of wastewaters and also pollution accumulating in the bottom sediment. The nutrient-limiting elements in the water lake quality are determined with TN/TP ratio. Accordingly, the lake water quality was determined as N-limited at two points and co-limited at three points. The relationship between the nutrients was evaluated using regression analysis.

Substrate type selection in diatom based lake water quality assessment

Various studies report contrasting results on the substrate-type effect on diatom community composition, but the particularly important question is whether or not it affects diatom-based assessments of water quality. We investigated whether the substrate type is a significant predictor of the diatom community composition and if it affects lake water quality assessment based on diatom indices. This study took place in Sava Lake (Serbia). We used glass, ceramic, willow and yew tree tiles as artificial substrates for periphyton development, and pebbles from the lake littoral as natural substrate. Results revealed differences in both the diatom community composition and diatom indices values related to the substrates. A distinction was recognized between natural, artificial wooden, and artificial inert substrates. However, the final lake quality assessment based on diatom indices was more or less similar in all substrate types in our study, and depended on value ranges associated with water quality classification and on diatom index choices. Artificial substrates in our study did show potential as an alternative for natural substrate, but further studies are required, particularly in various types of lentic ecosystems to confirm our findings and support artificial substrate employment in lake water quality assessment.

Indicative Lake Water Quality Assessment Using Remote Sensing Images-Effect of COVID-19 Lockdown

The major lockdown due to the COVID-19 pandemic has affected the socio-economic development of the world. On the other hand, there are also reports of reduced pollution levels. In this study, an indicative analysis is adopted to understand the effect of lockdown on the changes in the water quality parameters for Lake Hussain Sagar using two remote sensing techniques: (i) spectral reflectance (SR) and (ii) chromaticity analysis (Forel-Ule color Index (FUI) and Excitation Purity). The empirical relationships from earlier studies imply that (i) increase in SR values (band B2) indicates a reduction in Chlorophyll-a (Chl-a) and Colored Dissolved Organic Matter (CDOM) concentrations, and (ii) increase in FUI indicates an increase in Total Suspended Solids (TSS). The Landsat 8 OLI satellite images are adopted for comparison between (i) January to May of year 2020: the effect of lockdown on water quality, and (ii) March and April for years 2015 to 2020: historical variations in water quality. The results show notable changes in SR values and FUI due to lockdown compared to before lockdown and after unlock suggesting a significant reduction in lake water pollution. In addition, the historical variations within April suggest that the pollution levels are least in the year 2020.

Understanding the Variability in Estimation of Water Quality of Lakes and Reservoirs

This paper presents a critical review on the existing methodology of water quality assessment of lakes and reservoirs being used as a source of water supply and irrigation purposes. The seasonal and depth-wise variations in water quality are also analysed and presented through two case studies. It is inferred that water quality monitoring is a helpful tool not only to evaluate the impacts of pollution sources but also to ensure an efficient management of water resources and the protection of aquatic life. However, it is incomplete to make any meaningful prediction without correlating the prevailing catchment characteristics as well as imparting the scope for real-time action plan. The present study highlights a few strategic features causing variability in water quality and proposes a corroborative plan to address those issues.

Estimating Chlorophyll-a of Inland Water Bodies in Greece Based on Landsat Data

Assessing chlorophyll-a (Chl-a) pigments in complex inland water systems is of key importance as this parameter constitutes a major ecosystem integrity indicator. In this study, a methodological framework is proposed for quantifying Chl-a pigments using Earth observation (EO) data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and 8 Operational Land Imager (OLI) sensors. The first step of the methodology involves the implementation of stepwise multiple regression (MLR) analysis of the available Chl-a dataset. Then, principal component analysis (PCA) is performed to explore Greek lakes’ potential interrelationships based on their Chl-a values in conjunction with certain criteria: their characteristics (artificial/natural), typology, and climatic type. Additionally, parameters such as seasonal water sampling and the date difference between sampling and satellite overpass are taken into consideration. Next, is implemented a stepwise multiple regression analysis among different groups of cases, formed by the criteria indicated from the PCA itself. This effort aimed at exploring different remote sensing-derived Chl-a algorithms for various types of lakes. The practical use of the proposed approach was evaluated in a total of 50 lake water bodies (natural and artificial) from 2013–2018, constituting the National Lake Network Monitoring of Greece in the context of the Water Framework Directive (WFD). All in all, the results evidenced the suitability of Landsat data when used with the proposed technique to estimate log-transformed Chl-a. The proposed scheme resulted in the development of models separately for natural (R = 0.78; RMSE = 1.3 μg/L) and artificial lakes (R = 0.76; RMSE = 1.29 μg/L), while the model developed without criteria proved weaker (R = 0.65; RMSE = 1.85 μg/L) in comparison to the other ones examined. The methodological framework proposed herein can be used as a useful resource toward a continuous monitoring and assessment of lake water quality, supporting sustainable water resources management.

Assessment of Lake Water Quality and Eutrophication Risk in an Agricultural Irrigation Area: A Case Study of the Chagan Lake in Northeast China

Water quality safety is the key factor to maintain the ecosystem service functions of lakes. Field investigations and statistical analyses were carried out to study the water quality of a large, agriculture-stressed lakes (e.g., Chagan Lake) in Northeast China. The hydro-chemical properties of the Chagan Lake are HCO3·CO3-Na. Nutrient (N and P) and non-nutrient (pH and F−) were found to be the major factors that threaten water quality safety of the lake. The concentration of total nitrogen (TN) and total phosphorus (TP) was found to vary seasonally and at different locations. The overall lake water had mean TN and TP values of 2.19 mg/L and 0.49 mg/L, respectively, in summer. TN was the major factor for water quality deterioration in the western region of the lake, while TP was the principal factor in the other regions, as determined by a principal component analysis (PCA). Fluoride (F−) concentration in the lake water were related to the values of total dissolved solid (TDS), pH, and electrical conductivity (EC). In addition, eutrophication is a fundamental index that has been affecting the ecological evaluation of water quality. The results showed that trophic level index (TLI), trophic state index (TSI), and eutrophication index (EI) were evaluated to quantify the risk of eutrophication. However, TLI and TSI can better describe the purification effect of the wetland. These indices showed that the lake water was hyper-eutrophic in summer, with TLI, TSI, and EI values of 60.1, 63.0, and 66.6, respectively. Disparities in water quality were observed among whole areas of the lake. Overall, this study revealed that controlling agriculture drainage is crucial for lake water quality management. The study generated critical data for making water quality management plans to control the risk.

Contribution of 3D coupled hydrodynamic-ecological modeling to assess the representativeness of a sampling protocol for lake water quality assessment

This study deals with the impact of spatio-temporal heterogeneities on the assessment of lake ecological status according to the European water framework directive (WFD). A method, based on three-dimensional coupled hydrodynamic and ecological modeling, is presented to assess the variability of lake ecological status, and to locate the most representative sampling station of Lake Geneva (France/Switzerland). Five variables used in the lake ecological status evaluation were simulated by using the free software Delft3D. The numerical simulation results showed that the simulated ecological status based on chlorophyll a and total phosphorus concentrations measured at the regulatory monitoring station depend on the choice of the sampling date. Results also indicated a strong spatial heterogeneity in ecological status that varies from “poor” to “good” along an East-West gradient. Finally, the numerical simulation results showed that the most representative point of a mean theoretical ecological quality for Lake Geneva would be located in the center of the upper basin, close to the historical sampling station.

Pairing paleolimnological inference models with mechanistic water column models enhances assessment of lake water quality

Reconciliation of paleolimnology inference models with hindcasts from mechanistic water column models aided the reconstruction of past relationships for total phosphorus/dissolved oxygen and acid neutralizing capacity/pH in highly polluted lake ecosystems in New York State. Pre-disturbance Onondaga Lake, Syracuse, NY, was shown to have experienced seasonal hypolimnetic anoxia even under oligotrophic (<10 ug l−1) phosphorus levels. In the Adirondack Mountains of New York State the paired modeling confirmed that, while many lakes have the potential to eventually recover from acidification by atmospheric deposition, approximately 30% likely experienced naturally acidic conditions (pH < 6) prior to increases in industrial emissions. Comparison between the model results illuminated areas of individual model inadequacy, improved understanding of lake ecology, and increased confidence in the ability of predictive water column models to accurately develop restoration scenarios representing improved conditions. The work presented here is the first such comparison modeling for total phosphorus, dissolved oxygen, and acid neutralizing capacity. The technique remains to be more widely applied geographically and extended to less heavily stressed lake systems. Because a fossil inference and mechanistic hindcast should independently lead to similar results, comparison modeling is a potentially powerful tool for examining past interactions between ecosystem structure and ecosystem functioning.