3 resultados para Coastal monitoring

em Cochin University of Science


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An attempt is made to study the possible relationship between the process of upwelling and zooplankton biomass in the shelf weters along the south west coast of India between Cape comorin and Ratnagiri based on oceanographic and Zooplankton data collected by the erstwhile FAO/UNDP Pelagic Fishery Project,Cochin between 1973 and 1978. Different factors such as the depth from which the bottom waters are induced upwards during the process of upwelling,the depth to which the bottom waters are drawn, vertical velocity of upwelling and the resultant zooplankton productivity were considered while arriving at the deductions. Except for nutrients and phytoplankton productivity, for which simultaneous data is lacking, all the major factors were taken into consideration before cocluding- xon positive/negative correlation.

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Assessment water’ quality nowa-days in global scenario implies the need for a reference point against which monitoring can be measured and weighed. Aquatic ecosystenis as part of the natural environment are balanced both witliin tlicinselves and with other environmental compartments and this equilibrium is subject to natural variations and evolutions as well as variations caused by human intervention. The present assessnient is to identify. and possibly quantify, anthropogenic influences over time against a “natural baseline situation. Water pollution problems have only recently been taken seriously in retrospect. Once damage occurred, it becomes immeasurable, and control action cannot be initiated

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In situ methods used for water quality assessment have both physical and time constraints. Just a limited number of sampling points can be performed due to this, making it difficult to capture the range and variability of coastal processes and constituents. In addition, the mixing between fresh and oceanic water creates complex physical, chemical and biological environment that are difficult to understand, causing the existing measurement methodologies to have significant logistical, technical, and economic challenges and constraints. Remote sensing of ocean colour makes it possible to acquire information on the distribution of chlorophyll and other constituents over large areas of the oceans in short periods. There are many potential applications of ocean colour data. Satellite-derived products are a key data source to study the distribution pattern of organisms and nutrients (Guillaud et al. 2008) and fishery research (Pillai and Nair 2010; Solanki et al. 2001. Also, the study of spatial and temporal variability of phytoplankton blooms, red tide identification or harmful algal blooms monitoring (Sarangi et al. 2001; Sarangi et al. 2004; Sarangi et al. 2005; Bhagirathan et al., 2014), river plume or upwelling assessments (Doxaran et al. 2002; Sravanthi et al. 2013), global productivity analyses (Platt et al. 1988; Sathyendranath et al. 1995; IOCCG2006) and oil spill detection (Maianti et al. 2014). For remote sensing to be accurate in the complex coastal waters, it has to be validated with the in situ measured values. In this thesis an attempt to study, measure and validate the complex waters with the help of satellite data has been done. Monitoring of coastal ecosystem health of Arabian Sea in a synoptic way requires an intense, extensive and continuous monitoring of the water quality indicators. Phytoplankton determined from chl-a concentration, is considered as an indicator of the state of the coastal ecosystems. Currently, satellite sensors provide the most effective means for frequent, synoptic, water-quality observations over large areas and represent a potential tool to effectively assess chl-a concentration over coastal and oceanic waters; however, algorithms designed to estimate chl-a at global scales have been shown to be less accurate in Case 2 waters, due to the presence of water constituents other than phytoplankton which do not co-vary with the phytoplankton. The constituents of Arabian Sea coastal waters are region-specific because of the inherent variability of these optically-active substances affected by factors such as riverine input (e.g. suspended matter type and grain size, CDOM) and phytoplankton composition associated with seasonal changes.