Carlson's Trophic State Index Research Articles

Surface water quality assessment of Amingaon (Assam, India) using multivariate statistical techniques

Abstract The pollution of surface water has become a global environmental issue. Monitoring of surface water is essential to know the current status of water quality and maintain it at certain desirable level. In this study surface water quality of Amingaon has been analysed. Amingaon is a locality in North Guwahati (Assam, India). In last few decades’ the locality has undergone rapid and uncontrolled development activities which have a detrimental impact on its ecology and environment. Samples were collected from 12 lakes and analysed for 24 parameters namely temperature (T), pH, electrical conductivity (EC), turbidity (Tur), total suspended solids (TSS) and total dissolved solids (TDS), total alkalinity (TA), total hardness (TH), chloride ion (Cl−), fluoride (F−), sulphate (SO42−), sodium (Na+), potassium (K+), calcium (Ca2+), dissolved oxygen (DO) biochemical oxygen demand (BOD), chemical oxygen demand (COD), ammonium nitrogen (NH3-N), total Kjeldahl nitrogen (TKN), nitrate (NO3−) total phosphorus (TP) and available phosphorus (AP). Multivariate statistical techniques were used for the assessment of water quality. Cluster analysis (CA) was used for classification of water quality parameters and principal component analysis (PCA) was used to identify the sources of pollution. CA grouped all the water quality parameters in three cluster. PCA resulted in six useful components which explained 90.54% of the total variance. Based on overall study it was concluded that the sources of pollution of lakes were the use of fertilizers, storm water runoff, land development and domestic waste water discharge. Trophic state of lakes was also evaluated using Carlson's Trophic State Index (TSI).

Trophic state categorisation and assessment of water quality in Manjirenji Dam, Zimbabwe, a shallow reservoir with designated multi-purpose water uses

Intermittent, dire droughts and water abstraction pressures impact shallow man-made reservoirs with multiple designated water uses, often leading to water quality deterioration, and loss of biological integrity and utility value of a lake, threatening the livelihoods of lake shore communities. Thus, water quality information is crucial in setting up guidelines for freshwater resources management. In this study we investigated the water quality, determined the trophic state and assessed the influence of lake zones on the physical-chemical parameters of the Manjirenji Dam, Zimbabwe. Furthermore, we tested the applicability of two customary temperate water quality indices, the Canadian Council of Ministers of the Environment (CCME) Water Quality Index and the Carlson Trophic State Index, for a tropical lake system. Ten littoral and seven pelagic sites were sampled monthly over 9 months for the following water parameters: pH, conductivity, turbidity, total dissolved solids, suspended solids, chlorophyll a , temperature, dissolved oxygen, water transparency, ammonia, nitrogen, nitrates, total and reactive phosphorus. Despite slight fluctuations/variations, water quality in the Manjirenji Dam was generally fair, with a CCME value averaging 78.1, and the Carlson Trophic State Index reflecting oligotrophy. Non-significant differences in water quality parameters between pelagic and littoral sites in the Manjirenji Dam reflect the high connectivity of different spatial zones in a shallow lentic system. Index scores of the adapted temperate water indices detect similar water quality conditions for the Manjirenji Dam, thus perhaps indicating their potential applicability. The current water quality data set for the Manjirenji Dam is vital for formulating prudent management strategies to formulate/ensure adequate multi-purpose water usage and service for this aquatic ecosystem. Keywords: ecotone, lake zones, water quality, trophic state, Manjirenji Dam

Ecological assessment of East Hammar marsh, Iraq using a number of ecological guides

The ecological status of the East Hammar marsh was evaluated by using a number of ecological guides: water quality index (WQI), Carlson trophic state index (TSI) and fish integrated biological index (F-IBI) during the period from November 2012 to October 2013. The results revealed that the annual value of WQI varied from 51.1 (marginal) for historical data before desiccation to 67.8 (fair) for data after inundation. The marsh was evaluated to be mesotrophic (TSI= 42.0). IBI scores were calculated from 16 separate assemblage metrics based on the fish species richness, species composition and trophic guilds. The ecological status of the marsh was found to be fair (F-IBI= 47.7) and was slightly better than the status of the marsh after 2-4 years of restoration activities. The rather low improvement in the situation of the marsh indicates that the environment is still fragile and requires the allocation of water share from the Tigris and Euphrates rivers to restore marsh normality.

Sensoriamento remoto como ferramenta de monitoramento da qualidade da água do Lago Paranoá (DF)

RESUMO: Este trabalho testou uma metodologia baseada no sensoriamento remoto para estimar o estado trófico de um reservatório urbano (Lago Paranoá) em Brasília (Brasil), com vistas ao monitoramento da qualidade da água. Quatro fases limnológicas do Lago Paranoá foram analisadas a partir da eutrofização do reservatório como resultado do excessivo aporte de esgotos domésticos. Dados de fósforo total, clorofila-a , transparência da água e imagens processadas do LANDSAT TM 5 foram utilizados para estimar do estado trófico. Esses dados foram correlacionados com dados limnológicos e os mapas quantificaram as variáveis para todo o espelho d'água. Com o uso do Índice de Estado Trófico de Carlson, novos mapas foram gerados, estimando o estado trófico do Lago Paranoá para cada fase limnológica analisada. O método e as estimativas testadas mostraram-se adequados para o monitoramento da qualidade da água, pois refletem as mudanças que a água do reservatório experimentou após a eutrofização.

Assessing ecological water quality of freshwaters: PhyCoI—a new phytoplankton community Index

We propose and test a new Phytoplankton Community Index (PhyCoI) for monitoring the ecological status of lakes and reservoirs. The design of our PhyCoI is based on the fact that phytoplankton biomass and community structure respond to changes in water quality (mainly eutrophication) and by themselves also influence water quality. In order to accommodate this double role of phytoplankton as indicator and impact, PhyCoI is based on phytoplankton community properties at different hierarchical levels combining both specific metrics (total biomass, taxonomic group biomass, cyanobacteria contribution, taxonomic group species richness) and new or modified sub-indices. It is calculated from the scores of the different metrics/sub-indices resulting in a final index value in the range from 0 to 5, to assess water quality on the basis of five ecological classes according to the Water Framework Directive (WFD). The test of PhyCoI was based on Carlson's Trophic State Index (TSISD) based on water transparency (Secchi depth) in 26 Greek lakes and reservoirs covering the entire spectrum from oligotrophic to hypertrophic. A highly significant relationship at p<0.001 between the two variables was found, with the values of the PhyCoI declining with increasing TSISD. Furthermore, a significant relationship between the PhyCoI and land use types at the watershed of the studied freshwaters was found identifying permanent crops, pastures and shrubs and herbaceous vegetation associations as significant predictors of PhyCoI values. Because of the amount of labor involved in obtaining the PhyCoI we suggest to combine low frequency PhyCoI determinations with a high frequency Secchi depth measurements for practical monitoring purposes.

Applying the Back-Propagation Neural Network model and fuzzy classification to evaluate the trophic status of a reservoir system.

The trophic state index, and in particular, the Carlson Trophic State Index (CTSI), is critical for evaluating reservoir water quality. Despite its common use in evaluating static water quality, the reliability of the CTSI may decrease when water turbidity is high. Therefore, this study examines the reliability of the CTSI and uses the Back-Propagation Neural Network (BPNN) model to create a new trophic state index. Fuzzy theory, rather than binary logic, is implemented to classify the trophic status into its three grades. The results show that compared to the CTSI with traditional classification, the new index with fuzzy classification can improve trophic status evaluation with high water turbidity. A reliable trophic state index can correctly describe reservoir water quality and allow relevant agencies to address proper water quality management strategies for a reservoir system.

Mathematical Modeling of Trophic State and Nutrient Flows of Lake Karla using the PCLake Model

In the present article, we simulate Lake Karla, an important natural ecosystem under restoration in Greece, operating also as a reservoir. The lake trophic state is characterized as hypertrophic with the expected negative effects on biodiversity. The simulation of Lake Karla is a significant tool in terms of understanding, predicting and managing the ecosystem. We perform simulations using PCLake, a software package for shallow lakes, which provides a full set of parameters, modeling a wide range of physical, chemical and biological variables. The model is calibrated based on the time series of six variables for year 2012 and validated using data of years 2014–2015. We present the nutrient flow dynamics for year 2012 on a trimester basis, and investigate the interrelations of nutrient cycling and trophic state, through observed variables such as phycocyanin and chlorophyll-a concentrations, Carlson Trophic State Index and ratio of Dissolved Inorganic Nitrogen to Soluble Reactive Phosphorus.

Seasonal variation of Legionella in Taiwan's reservoir and its relationships with environmental factors.

In this study, the presence of Legionella in major water reservoirs of Taiwan was examined with respect to seasonal variation, geographical variation, and water quality parameters using TaqMan real-time qPCR. Water samples were collected quarterly at 19 reservoirs in Taiwan between November 2012 and August 2013. The detection rate for Legionella was 35.5% (27/76), and Legionella was detected in all seasons. The Legionella concentration was relatively high in spring and summer, reaching 3.86 × 10(8) and 7.35 × 10(8) cells/L, respectively. By sampling the area, Legionella was detected at a higher proportion in reservoirs in the northern and southern areas, and the difference was consistent in all seasons. Significant association was found between detection of Legionella and various water quality parameters, including conductivity, chlorophyll a, and dissolved oxygen (Mann-Whitney U test, P < 0.05). Results of Spearman rank test showed negative correlation for Legionella detection with pH (P = 0.030, R = -0.497) and dissolved oxygen (P = 0.007, R = -0.596) in fall and positive correlation with Carlson's trophic state index (P = 0.049, R = 0.457) in spring. The identified species included Legionella pneumophila and Legionella drancourtii. The detection of Legionella in reservoirs was indicative of a potential public health risk and should be further evaluated.

Lakes of Malaysia: Water quality, eutrophication and management

AbstractThe present study was undertaken to evaluate and verify the water quality status and trophic state of 15 major lakes and reservoirs in Malaysia. The lake water quality assessments were based on the National Water Quality Index (NWQI), while the trophic state assessments were based on Carlson's Trophic State Index (TSI). The findings of this water quality assessment, based on data collected between September and October 2012, indicated that a majority of the lakes were classified as Class II (Clean) waters suitable for recreational use. The results of the trophic state assessments, however, indicated that all of the lakes were eutrophic, meaning they were nutrient‐rich, they could experience algae blooms or macrophyte problems, and they were likely to exhibit poor water quality. Sustainable management measures and strategies are suggested to address the eutrophication problems of Malaysian lakes and reservoirs, with the national responses on lake and reservoir management also being discussed.

The trophic status of Suwałki Landscape Park lakes based on selected parameters (NE Poland)

This study describes changes in the trophic status of 12 lakes within Suwałki Landscape Park (SLP). All of the trophic classifications of the lakes were based on the trophic continuum division. Trophic status was determined by means of multiparameter indices using several diverse criteria. In this study, the assessment of the trophic status of lakes included water quality; abundance and biomass of bacterioplankton, phytoplankton, and zooplankton; and primary production of phytoplankton. The Carlson trophic state index (TSI) describes the level of water fertility and indicated the dominance of moderately eutrophic waters. Lakes Perty, Jeglówek, and Hańcza have a trophic status that indicates mesotrophy (TSI <50). The trophic status of the studied lakes was determined based on the bacterial abundance and clearly showed a lack of oligotrophic lakes in SLP. Based on the number of bacteria, only Lake Szurpiły can be classified as β-mesotrophic, whereas Lake Linówek can be characterized as hypertrophic with some features typical for humic waters. The greatest value of gross primary production was observed in Lake Linówek (126.4 mg C/m3/h). The phytoplankton trophy index varied from 1.59 to 2.28, and its highest value, which indicated eutrophy, was determined for Lake Udziejek. In the case of Lakes Hańcza, Szurpiły, Perty, Jeglówek, and Kojle, the index ranged from 1.25 to 1.74, which indicated mesotrophy. The majority of the lakes were classified as mesoeutrophic (1.75–2.24). The highest trophic status was assessed for lakes with a marked dominance of cyanobacteria (Lake Przechodnie, Lake Krajwelek, Lake Udziejek, and Lake Pogorzałek), which is commonly recognized as an indicator of high trophic status. Considering all of the indices of trophic status, the analysis of rotifer community structure indicates that the studied group of lakes is mesoeutrophic or eutrophic. The values of crustacean zooplankton indices indicated that the trophic status of the studied lakes was close to that determined using a TSI. The parameters of zooplankton abundance and species structure allowed for the observance of changes in the tropic levels of lakes, which are difficult to detect by a chemical assay alone.

Investigation on trophic state index by artificial neural networks (case study: Dez Dam of Iran)

Dam construction and surface runoff control is one of the most common approaches for water-needs supply of human societies. However, the increasing development of social activities and hence the subsequent increase in environmental pollutants leads to deterioration of water quality in dam reservoirs and eutrophication process could be intensified. So, the water quality of reservoirs is now one of the key factors in operation and water quality management of reservoirs. Hence, maintaining the quality of the stored water and identification and examination of changes along time has been a constant concern of humans that involves the water authorities. Traditionally, empirical trophic state indices of dam reservoirs often defined based on changes in concentration of effective factors (nutrients) and its consequences (increase in chlorophyll a), have been used as an efficient tool in the definition of dam reservoirs quality. In recent years, modeling techniques such as artificial neural networks have enhanced the prediction capability and the accuracy of these studies. In this study, artificial neural networks have been applied to analyze eutrophication process in the Dez Dam reservoir in Iran. In this paper, feed forward neural network with one input layer, one hidden layer and one output layer was applied using MATLAB neural network toolbox for trophic state index (TSI) analysis in the Dez Dam reservoir. The input data of this network are effective parameters in the eutrophication: nitrogen cycle parameters and phosphorous cycle parameters and parameters that will be changed by eutrophication: Chl a, SD, DO and the output data is TSI. Based on the results from estimation of modified Carlson trophic state index, Dez Dam reservoir is considered to be eutrophic in the early July to mid-November and would be mesotrophic with decrease in temperature. Therefore, a decrease in water quality of the dam reservoir during the warm seasons is expectable. The results indicated that artificial neural network (ANN) is a suitable tool for quality modeling of reservoir of dam and increment and decrement of nutrients in trend of eutrophication. Therefore, ANN is a suitable tool for quality modeling of reservoir of dam.

Modeling Impreciseness of Trophic State Levels for Eutrophication Assessment

Tremendous efforts have been madeto propose numerous indices for quantifyingstates of eutrophication in lentic water bodies over the last decades. Most of the indices are developed or modified considering conventional trophic state indices (e.g., Carlson trophic state index (TSI)) or pre-specified ranges of cause and response variables (e.g., index proposed by Organization of Economic and Cooperation and Development (OECD)), where a strong correlation structure must exist among cause and response variables. Here an attempt is made to model impreciseness or subjectivity of trophic state levels,especially for weakly correlated variables. A generalized framework using fuzzy synthetic evaluation (FSE), analytic hierarchy process (AHP) and the concept of statistical entropyis proposed to assess the trophic state of lentic water bodies. The proposed methodology has been tested with the case study of Jordan lake data set collected from the United States of Geological Survey (USGS) data base.The result shows that, the eutrophication problem is critical mostly during the months of August to October,and the method can efficiently capture the rapid changes in trophic states.The sensitivity of the model has been tested with different weight structures for cause and response variables considered during model development, and the robustness of the model has also been tested with different weighting techniques.

Investigation on the trophic status of Ekbatan reservoir: a drinking water supply reservoir in Iran.

Eutrophication is one of the detrimental environmental problems in water reservoirs dye to the irregular introducing nutrients (phosphorus and nitrogen). This study aimed to explore the eutrophication state of Ekbatan Reservoir, Hamadan, western Iran. Monthly sampling was conducted during April 2010 to March 2011. Seven sampling stations were selected in the various locations of the reservoir and the samples were collected in the depth of 50 cm. The grab sampling of water for nitrogen, phosphorous and chlorophyll-a was carried out at all localities by Hatch sampler. The trophic state of the dam was determined by Carlson's Trophic State Index (TSI) and Chapra's classification. The highest concentrations of phosphorus and chlorophyll-a were measured in August and the lowest concentration for both of the parameters was determined in February. The TSI index according phosphorus concentration showed that the reservoir was in eutrophic status during May to November and was in mesotrophic status over November to May. It seems that the eutrophication process in the lake was resulted from the rural wastewaters and agricultural fertilizers. Therefore, using long term management methods including prevent of uncontrolled discharge of agricultural wastewaters is recommended in order to reduce the eutrophication in the reservoir. Decrease of phosphorus concentration in the dam by 50% can convert the eutrophic state to mesotrophic state.

Effects of environmental factors on nutrients release at sediment-water interface and assessment of trophic status for a typical shallow lake, northwest China.

Surface sediment and water samples were collected from Daihai Lake to study the biogeochemical characteristics of nitrogen and phosphorus, to estimate the loads of these nutrients, and to assess their effects on water quality. The contents and spatial distributions of total phosphorus (TP), total nitrogen (TN), and different nitrogen forms in sediments were analyzed. The results showed that concentrations of TN and TP in surface sediments ranged from 0.27 to 1.78 g/kg and from 558.31 to 891.29 mg/kg, respectively. Ratios of C : N ranged between 8.2 and 12.1, which indicated that nitrogen accumulated came mainly from terrestrial source. Ratios of N : P in all sampling sites were below 10, which indicated that N was the limiting nutrient for algal growth in this lake. Effects of environment factors on the release of nitrogen and phosphorus in lake sediments were also determined; high pH values could encourage the release of nitrogen and phosphorus. Modified Carlson's trophic state index (TSIM) and comprehensive trophic state index (TSIC) were applied to ascertain the trophic classification of the studied lake, and the values of TSIM and TSIC ranged from 53.72 to 70.61 and from 47.73 to 53.67, respectively, which indicated that the Daihai Lake was in the stage of hypereutropher.

Seasonal dynamic and spatial distribution of chlorophyll-a concentration in Lake Erhai

2010年5月至2011年4月,对洱海叶绿素a的季节动态、空间分布及其与环境因子的关系进行研究.结果表明,水体中叶绿素a浓度存在明显的季节变化,其变化范围为4.11~24.30μg/L,年平均值为10.4±6.5μg/L,最小值出现在2011年3月,最大值出现在2010年9月.叶绿素a浓度在夏、秋季较高,冬、春季较低.在空间变化上,叶绿素a浓度在南部湖区最大,其次是北部湖区,中部湖区最低.Pearson相关系数和主成分分析表明,洱海叶绿素a浓度在不同湖区中与水温和透明度均呈极显著相关.总氮在北部和南部湖区与叶绿素a浓度均存在一定的相关性,而总磷与叶绿素a浓度在南部湖区存在一定的相关性.根据修正的卡尔森营养状态指数,洱海综合TSI值为50.6,水质处于中营养状态.;Seasonal dynamics and spatial distributions of chlorophyll-a concentration and its relationship to environmental factors in Lake Erhai from May 2010 to April 2011 were investigated. Results showed that the seasonal dynamics of chlorophyll-a concentration in Lake Erhai were obvious, ranging from 4.11 to 24.30 μg/L and with the annual mean value 10.4 ± 6.5 μg/L. The minimum and maximum of chlorophyll-a concentration appeared in March and September, respectively. The chlorophyll-a concentrations were much higher in summer and autumn while relatively lower in winter and spring. Spatially, chlorophyll-a concentrations were the highest in the southern zones of the lake, followed by the northern and the middle zones. Pearson correlations and principal component analysis suggested that the chlorophyll-a concentration has negative correlation with transparency in different zones of Lake Erhai, while has positive correlation with water temperature. The chlorophyll-a concentration was correlated significantly with total nitrogen in the northern and southern zones of Lake Erhai, while correlated with total phosphorus in southern zones. Based on the modified Carlson trophic state index, the comprehensive TSI was 50.6 in Lake Erhai, indicating a mesotrophic state.

Pollution Source Investigation and Water Quality Management in the Carp Lake Watershed, Taiwan

AbstractIn this study, a full survey of pollutant sources and water quality was conducted, followed by the application of a water quality model (Water Quality Analysis Simulation Program, WASP) to establish strategies of water quality control in Carp Lake, Taiwan. Results of the field investigation show that both point and non‐point source (NPS) pollutants were responsible for the poor water quality. The contributions of biochemical oxygen demand (BOD) from point source and NPS pollution were 45.9 and 55.1%, respectively. About 80% of total phosphorus (TP) were contributed by NPS. Additionally, point source and NPS pollution discharged 55.5 and 44.5% of NH3–N load, respectively. The Carlson's Trophic State Index ranged from 61.9 to 69.2 showing serious eutrophic problems in Carp Lake. The calculated BOD, NH3–N, and TP carrying capacity were approximately 2.8, 0.42, and 0.15 kg per day, respectively. However, the current pollutant loadings are approximately 3.0–5.5 times the calculated carrying capacity. With the help of the calibrated WASP model, remedial strategies for the lake water from short‐term to long‐term were developed. The completion of the small local sewer system to remove 80% of the point source pollution can serve as a short‐term goal while 40–60% of NPS removal by natural treatment systems may serve as a mid‐term goal. Furthermore, 80% of both source point and NPS pollution removal can be considered as a long‐term strategy. Results of heavy metal analysis show that the enriched sediment would be safe for agricultural applications.

Hyperspectral Remote Sensing of Total Phosphorus (TP) in Three Central Indiana Water Supply Reservoirs

The connection between nutrient input and algal blooms for inland water productivity is well known but not the spatial pattern of water nutrient loading and algae concentration. Remote sensing provides an effective tool to monitor nutrient abundances via the association with algae concentration. Twenty-one field campaigns have been conducted with samples collected under a diverse range of algal bloom conditions for three central Indiana drinking water bodies, e.g., Eagle Creek Reservoir (ECR), Geist Reservoir (GR), and Morse Reservoir (MR) in 2005, 2006, and 2008, which are strongly influenced anthropogenic activities. Total phosphorus (TP) was estimated through hyperspectral remote sensing due to its close association with chlorophyll a (Chl-a), total suspended matter, Secchi disk transparency (SDT), and turbidity. Correlation analysis was performed to determine sensitive spectral variables for TP, Chl-a, and SDT. A hybrid model combining genetic algorithms and partial least square (GA-PLS) was established for remote estimation of TP, Chl-a, and SDT with selected sensitive spectral variables. The result indicates that TP has close association with diagnostic spectral variables with R 2 ranging from 0.55 to 0.72. However, GA-PLS has better performance with an average R 2 of 0.87 for aggregated dataset. GA-PLS was applied to the airborne imaging data (AISA) to map spatial distribution of TP, Chl-a, and SDT for MR and GR. The eutrophic status was evaluated with Carlson trophic state index using TP, Chl-a, and SDT maps derived from AISA images. Mapping results indicated that most MR belongs to mesotrophic (48.6%) and eutrophic (32.7%), while the situation was more severe for GR with 57.8% belongs to eutrophic class, and more than 40% to hypereutrophic class due to the high turbidity resulting from dredging practices.

Water quality changes in floodplain lakes due to the Amazon River flood pulse: Lago Grande de Curuaí (Pará)

Assurance of water quality for human consumption is essential for public health policies. In the Amazon floodplain, the seasonal water level variation causes periodic flooding of marginal areas that are usually used for settlements, agriculture and livestock. Therefore, the exchange of materials between the terrestrial and aquatic ecosystem affects the proportion of suspended and dissolved components in water and its physical-chemical characteristics, and consequently the quality of the water used by local people. Following this approach, the aim of this study is to evaluate changes in water quality in Lago Grande de Curuaí floodplain, Óbidos, Pará in response to the flood pulse, during one hydrological year from 2003 to 2004, based on water use classes (according to National Water Agency 357/2005 resolution) using chlorophyll-a and dissolved oxygen concentration as parameters and the eutrophication index. Ordinary kriging was applied to interpolate chlorophyll-a and dissolved oxygen and to predict values at non sampled locations. Each location was then classified according to water use acceptable parameters and to Carlson Trophic State Index modified by Toledo to map lake water classes and trophic status. The result showed that Lago Grande de Curuaí floodplain is a supereutrophic system, with levels of dissolved oxygen and chlorophyll-a not suitable for human supply during the receding water phase. These areas are located near the riverine communities, which can cause health problems due to the presence of potentially toxic algae. Therefore, monitoring water quality in Amazon lakes is essential to ensure the availability has appropriate quality for human and animal supplies.

Environmental status of a tropical lake system

Eutrophication has become a serious threat to the lake systems all over the world. This is mainly due to the pollution caused by anthropogenic activities. Carlson trophic state index (CTSI) is commonly used for the classification of trophic conditions of surface waters. The study is conducted to assess the trophic status of a tropical lake (Akkulam-Veli lake, Kerala, India) using CTSI based on Secchi disc depth (SD), total phosphorus (TP) and chlorophyll-a. The TSI values based on SD and TP are high (>70), indicating the hypereutrophic state which needs urgent action for the restoration of the fragile ecosystem. The higher TP in both lakes, and the lower value of chlorophyll-a in the Akkulam part, warrant explanation, are discussed here. The influence of other biochemical parameters in both the Akkulam and the Veli part of the lake has been assessed. Correlation analysis is conducted to study the effect of various water quality parameters. The variation in the water quality before and after the opening of sand bar is studied using paired t test. As almost all the lakes in the world are experiencing similar situation of extinction, this study is helpful to have an insight in the hydrochemistry of the lake as well as to identify the worst affected areas of the lakes.

Trophic state index of a lake system using IRS (P6-LISS III) satellite imagery

Water pollution has now become a major threat to the existence of living beings and water quality monitoring is an effective step towards the restoration of water quality. Lakes are versatile ecosystems and their eutrophication is a serious problem. Carlson Trophic State Index (CTSI) provides an insight into the trophic condition of a lake. CTSI has been modified for the study area and is used in this study. Satellite imagery analysis now plays a prominent role in the quick assessment of water quality in a vast area. This study is an attempt to assess the trophic state index based on secchi disk depth and chlorophyll a of a lake system (Akkulam-Veli lake, Kerala, India) using Indian Remote Sensing (IRS) P6 LISS III imagery. Field data were collected on the date of the overpass of the satellite. Multiple regression equation is found to yield superior results than the simple regression equations using spectral ratios and radiance from the individual bands, for the prediction of trophic state index from satellite imagery. The trophic state index based on secchi disk depth, derived from the satellite imagery, provides an accurate prediction of the trophic status of the lake. IRS P6-LISS III imagery can be effectively used for the assessment of the trophic condition of a lake system.