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Thiruvananthapuram, India

Sheela A.M.,Kerala State Pollution Control Board | Sarun S.,United Nations Development Programme | Justus J.,St Xaviers College | Vineetha P.,Kerala University | Sheeja R.V.,Kerala State Remote Sensing Agency
Environmental Geochemistry and Health | Year: 2015

Vector borne diseases are a threat to human health. Little attention has been paid to the prevention of these diseases. We attempted to identify the significant wetland characteristics associated with the spread of chikungunya, dengue fever and malaria in Kerala, a tropical region of South West India using multivariate analyses (hierarchical cluster analysis, factor analysis and multiple regression). High/medium turbid coastal lagoons and inland water-logged wetlands with aquatic vegetation have significant effect on the incidence of chikungunya while dengue influenced by high turbid coastal beaches and malaria by medium turbid coastal beaches. The high turbidity in water is due to the urban waste discharge namely sewage, sullage and garbage from the densely populated cities and towns. The large extent of wetland is low land area favours the occurrence of vector borne diseases. Hence the provision of pollution control measures at source including soil erosion control measures is vital. The identification of vulnerable zones favouring the vector borne diseases will help the authorities to control pollution especially from urban areas and prevent these vector borne diseases. Future research should cover land use cover changes, climatic factors, seasonal variations in weather and pollution factors favouring the occurrence of vector borne diseases. © 2014, Springer Science+Business Media Dordrecht. Source


Sheela A.M.,Kerala State Pollution Control Board | Letha J.,Directorate of Technical Education | Joseph S.,Kerala University | Thomas J.,Kerala University
Lakes and Reservoirs: Research and Management | Year: 2012

The study of the spatiotemporal variation of heavy metals in lake sediments is of great importance because heavy metals can result in toxic effects on aquatic biota through bioaccumulation. This study was undertaken to evaluate the degree of heavy metal contamination in the lacustrine sediments and the corresponding environmental deterioration in a tropical, urban, coastal lake (Akkulam-Veli), located in Kerala, India. The spatiotemporal variations of the cadmium (Cd), chromium (Cr), copper (Cu), lead (Pb), manganese (Mn), nickel (Ni) and zinc (Zn) concentrations in the lake sediments, as well as various indices of anthropogenic contamination, including Contamination Factor (CF), Pollution Load Index and Geoaccumulation Index (Igeo), were used to assess the degree of contamination. This study indicated contamination of the lake sediments with Cu, Pb and Zn. Urban domestic sewage and land run-off are the major drivers of the heavy metal loads to the lake. During the pre-monsoon, sediment contamination occurs in the upstream portion of Akkulam Lake because of a high clay content in the sediments. During the monsoon period, Akkulam Lake and the upstream portion of Veli Lake exhibit sediment contamination owing to high silt content. Domestic sewage is the main source of copper and zinc to the lake. Sewage bypass into the drains in the lake basin is largely responsible for the copper and zinc sediment contamination. High traffic levels and wastewater discharges from service stations/workshops are the main cause of the Pb loads entering the lake. Rubber particles of vehicle tires contain zinc and copper pigments that can accumulate on the surface of busy streets, entering the drains during rainfall events. Based on these study results, the accumulation of copper, zinc and lead in lake sediment can be controlled to a great extent by restricting the above-noted activities. As the sediment content of lead, zinc and copper is confined to the clay fraction during the non-rainy season and to the silt fraction during other seasons, lake restoration work should largely incorporate treating the clay and silt fractions, respectively, during both the non-rainy season and rainy season. © 2012 The Authors. Journal compilation © 2012 Blackwell Publishing Asia Pty Ltd. Source


Albert Moses S.,Kerala State Pollution Control Board | Janaki L.,Cochin University of Science and Technology | Joseph S.,Kerala University | Joseph J.,St Xaviers College
Lakes and Reservoirs: Research and Management | Year: 2016

The ability to predict water quality is a major requirement for planning and execution of developmental projects. It helps entrepreneurs to effectively plan and implement pollution control measures. This study evaluates the ability of different water quality models (statistical; remote sensing; mathematical) to predict salinity in Akkulam–Veli Lake, a tropical lake system. The performance of these three water quality models was evaluated. Prediction of salinity was made accurately with the mathematical model (WASP), compared to the other models. WASP facilitates prediction of daily water quality variations, which is not possible with the other models. A limitation of this model, however, was its ability to predict only a few water quality parameters. The statistical methods are reliable when the number of sampling sites and frequency of sample collection are high, making this method exhaustive and expensive. Remote sensing techniques proved to be less tedious, but are suitable only under specific situations, and not able to produce a high level of accuracy. Nevertheless, this method provides a continuous picture of spatial variations of different water quality parameters to a reasonable level of accuracy. The choice of the ‘best’ model varies on the basis of climatic and field conditions of the lake system of concern. Thus, a combination of water quality models was found to be the most ideal approach for analysing water quality data. © 2016 John Wiley & Sons Australia, Ltd Source


Albert Moses S.,Kerala State Pollution Control Board | Janaki L.,Directorate of Technical Education | Joseph S.,Kerala University | Kizhur Kandathil R.,Center for Earth Science Studies
Lakes and Reservoirs: Research and Management | Year: 2014

Lakes are versatile ecosystems, with eutrophication being a serious problem affecting their condition and trophic status. Eutrophication can lead to an over-abundance of macrophytes in lakes, producing favourable conditions for mosquito larvae. Increased eutrophication is attributed in most to excessive phosphorus concentrations in lake water. Satellite imagery analysis now plays a prominent role for quickly assessing water quality over a large area. The present study is an attempt to illustrate the variation of phosphate and total phosphorus concentrations in Akkulam-Veli Lake, Kerala, India, using Indian Remote Sensing satellite (IRS P6- LISS III) imagery. A multiple regression equation derived using radiance in the red and MIR bands in the imagery was found to yield superior results for predicting the phosphate concentration, whereas a simple regression equation using radiance in red band was found to yield good results for the total phosphorus concentration in lake water. Accordingly, the trophic status of the lake system can be determined easily from satellite imagery in this manner. © 2014 Wiley Publishing Asia Pty Ltd. Source


Sheela A.M.,Kerala State Pollution Control Board | Letha J.,Directorate of Technical Education | Joseph S.,Kerala University | Ramachandran K.K.,Center for Earth Science Studies | Chacko M.,Kerala University
International Journal of Applied Earth Observation and Geoinformation | Year: 2012

Lakes are versatile ecosystems and they are under the threat of eutrophication and siltation. The physical characteristics of a lake provide some insight into the status of the lake. Satellite imagery analysis now plays a prominent role in the quick assessment of characteristics of a lake system in a vast area. This study is an attempt to assess the water temperature, depth, and turbidity level of a lake system (Akkulam-Veli lake, Kerala, India) using IRS P6-LISS-III imagery. Field data were collected on the date of the overpass of the satellite. For the assessment of water temperature from satellite imagery, regression equation using spectral ratio (green/red bands) is found to yield superior results than the simple regression equation and multiple regression equation. For predicting the water depth, radiance in green and red bands can be used whereas that for turbidity, radiance in green and SWIR can be used. IRS P6-LISS-III imagery can be effectively used for the assessment of the physical characteristics of a lake system at a low cost. © 2011 Elsevier B.V. Source

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