4 resultados para Coastal and nearshore sediments

em Indian Institute of Science - Bangalore - Índia


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For the analysis and design of pile foundation used for coastal structures the prediction of cyclic response, which is influenced by the nonlinear behavior, gap (pile soil separation) and degradation (reduction in strength) of soil becomes necessary. To study the effect of the above parameters a nonlinear cyclic load analysis program using finite element method is developed, incorporating the proposed gap and degradation model and adopting an incremental-iterative procedure. The pile is idealized using beam elements and the soil by number of elastoplastic sub-element springs at each node. The effect of gap and degradation on the load-deflection behavior. elasto-plastic sub-element and resistance of the soil at ground-line have been clearly depicted in this paper.

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We present here observations on diurnal and seasonal variation of mixing ratio and delta C-13 of air CO2, from an urban station-Bangalore (BLR), India, monitored between October 2008 and December 2011. On a diurnal scale, higher mixing ratio with depleted delta C-13 of air CO2 was found for the samples collected during early morning compared to the samples collected during late afternoon. On a seasonal scale, mixing ratio was found to be higher for dry summer months (April-May) and lower for southwest monsoon months (June-July). The maximum enrichment in delta C-13 of air CO2 (-8.04 +/- 0.02aEuro degrees) was seen in October, then delta C-13 started depleting and maximum depletion (-9.31 +/- 0.07aEuro degrees) was observed during dry summer months. Immediately after that an increasing trend in delta C-13 was monitored coincidental with the advancement of southwest monsoon months and maximum enrichment was seen again in October. Although a similar pattern in seasonal variation was observed for the three consecutive years, the dry summer months of 2011 captured distinctly lower amplitude in both the mixing ratio and delta C-13 of air CO2 compared to the dry summer months of 2009 and 2010. This was explained with reduced biomass burning and increased productivity associated with prominent La Nina condition. While compared with the observations from the nearest coastal and open ocean stations-Cabo de Rama (CRI) and Seychelles (SEY), BLR being located within an urban region captured higher amplitude of seasonal variation. The average delta C-13 value of the end member source CO2 was identified based on both diurnal and seasonal scale variation. The delta C-13 value of source CO2 (-24.9 +/- 3aEuro degrees) determined based on diurnal variation was found to differ drastically from the source value (-14.6 +/- 0.7aEuro degrees) identified based on seasonal scale variation. The source CO2 identified based on diurnal variation incorporated both early morning and late afternoon sample; whereas, the source CO2 identified based on seasonal variation included only afternoon samples. Thus, it is evident from the study that sampling timing is one of the important factors while characterizing the composition of end member source CO2 for a particular station. The difference in delta C-13 value of source CO2 obtained based on both diurnal and seasonal variation might be due to possible contribution from cement industry along with fossil fuel / biomass burning as predominant sources for the station along with differential meteorological conditions prevailed.

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Saltwater intrusion into coastal aquifers is a global issue, exacerbated by increasing demands for freshwater in coastal regions. This study investigates into the parametric analysis on saltwater intrusion in a conceptual, coastal, unconfined aquifer considering wide range of freshwater draft and anticipated sea level rise. The saltwater intrusion under various circumstances is simulated through parametric studies using MODFLOW, MT3DMS and SEAWAT. The MODFLOW is used to simulate the groundwater flow system under changing hydro-dynamics in coastal aquifer. To simulate solute transport MT3DMS and SEAWAT is used. The saltwater intrusion process has direct bearing on hydraulic conductivity and inversely related to porosity. It may also be noted that increase in recharge rate considered in the study does not have much influence on saltwater intrusion. Effect of freshwater draft at locations beyond half of the width of the aquifer considered has marginal effect and hence can be considered as safe zone for freshwater withdrawals. Due to the climate change effect, the anticipated rise in sea level of 0.88 m over a century is considered in the investigation. This causes increase in salinity intrusion by about 25%. The combined effect of sea level rise and freshwater draft (C) 2015 The Authors. Published by Elsevier B.V.

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Land surface temperature (LST) is an important variable in climate, hydrologic, ecological, biophysical and biochemical studies (Mildrexler et al., 2011). The most effective way to obtain LST measurements is through satellites. Presently, LST from moderate resolution imaging spectroradiometer (MODIS) sensor is applied in various fields due to its high spatial and temporal availability over the globe, but quite difficult to provide observations in cloudy conditions. This study evolves of prediction of LST under clear and cloudy conditions using microwave vegetation indices (MVIs), elevation, latitude, longitude and Julian day as inputs employing an artificial neural network (ANN) model. MVIs can be obtained even under cloudy condition, since microwave radiation has an ability to penetrate through clouds. In this study LST and MVIs data of the year 2010 for the Cauvery basin on a daily basis were obtained from MODIS and advanced microwave scanning radiometer (AMSR-E) sensors of aqua satellite respectively. Separate ANN models were trained and tested for the grid cells for which both LST and MVI were available. The performance of the models was evaluated based on standard evaluation measures. The best performing model was used to predict LST where MVIs were available. Results revealed that predictions of LST using ANN are in good agreement with the observed values. The ANN approach presented in this study promises to be useful for predicting LST using satellite observations even in cloudy conditions. (C) 2015 The Authors. Published by Elsevier B.V.