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Stable isotope ratios of oxygen (δ18O) and carbon (δ13C) in tests ofGloborotalia menardii from samples at 25 cm intervals of top 900 cm cores, representing different thicknesses of the Pleistocene, from DSDP Sites
219, 220 and 241 in the northern Indian Ocean have been measured. Based on the δ18O stratigraphy, glacial and interglacial phases during the Pleistocene have been recognized, which are in good agreement with
the standard Quaternary planktonic foraminiferal/climatic zones i.e., Ericson zones at these sites, based onG. menardii abundances. The GIA (glacial interglacial amplitude) at Sites 241, 219 and 220 are of the order of 1·2, 1·4 and 1·9‰ respectively.
The last glacial and interglacial maxima (18 ka BP and 125 ka BP respectively) could be identified in DSDP Cores 241, and
219 with some precision. ‘Isotopic ages’ could be assigned to the different levels of these core sections based on the correlation
of δ18O record from these sites with the SPECMAP record (Imbrieet al 1984). Changes in sediment accumulation rates at different levels of the Pleistocene have been worked out on the basis of
changes in oxygen isotopic ratio.
Oscillations in δ13C stratigraphy at Site 241 indicated southwest monsoon induced increase in upwelling and productivity during warmer periods.
At Sites 219 and 220, variations in the δ13C record were due to the mixing of bottom water. 相似文献
87.
In the present study, growth and water relation parameters were analysed in drought-stressed Coriaria nepalensis Wall. seedlings. C. nepalensis seedlings were subjected to four drought cycles of 7, 14, 21, and 28-days, and to one control level (watered on alternate days) in a glasshouse. The seedlings failed to survive a 28-days drought during summer. Osmotic adjustment (defined as the decrease in osmotic potential at zero or full turgor in response to water deficit) was measured as the difference between the osmotic potential of seedlings watered on alternate days (control) and those subjected to 21-days drought cycle. Seedlings subjected to 21-days drought had a predawn water potential of −2.60 MPa, and showed an osmotic adjustment of −1.95 MPa at full turgor and −2.17 MPa at zero turgor. The growth of seedlings was positively related to moisture and with water potential. With decline in soil moisture the root:shoot ratio increased while leaf weight ratio decreased. Leaf characteristics, such as leaf number, leaf area, leaf area ratio, specific leaf area and leaf drop, were also affected by moisture stress. This study has indicated that osmotic adjustment is a major adaptive mechanism of C. nepalensis that aids successful regeneration of seedlings in degraded sites with inhospitable soil conditions. 相似文献
88.
A problem of reflection and transmission of elastic waves at a plane interface between a uniform elastic solid half-space and a porous elastic half-space containing two immiscible fluids is investigated. The theory developed by Lo, Sposito and Majer for porous media containing two immiscible fluids is employed to find out the reflection and transmission coefficients. The incident wave is assumed to propagate through the uniform elastic half-space and two cases are considered. In the first case, a beam of plane longitudinal wave is assumed to be incident and in the second case, a beam of transverse wave is assumed to be incident at the interface. By taking granite as impervious elastic medium and columbia fine sandy loam containing air-water mixture as porous medium, reflection and transmission coefficients are obtained. By neglecting the inertial coupling coefficients, these coefficients are reduced to those obtained by Tomar and Arora using the theory of Tuncay and Corapcioglu. It is found that the inertial coupling parameters significantly affect the phase speeds and the amplitude ratios of the transmitted waves. 相似文献
89.
Potential of support vector regression for prediction of monthly streamflow using endogenous property 总被引：2，自引：0，他引：2
In the recent past, a variety of statistical and other modelling approaches have been developed to capture the properties of hydrological time series for their reliable prediction. However, the extent of complexity hinders the applicability of such traditional models in many cases. Kernel‐based machine learning approaches have been found to be more popular due to their inherent advantages over traditional modelling techniques including artificial neural networks(ANNs ). In this paper, a kernel‐based learning approach is investigated for its suitability to capture the monthly variation of streamflow time series. Its performance is compared with that of the traditional approaches. Support vector machines (SVMs) are one such kernel‐based algorithm that has given promising results in hydrology and associated areas. In this paper, the application of SVMs to regression problems, known as support vector regression (SVR), is presented to predict the monthly streamflow of the Mahanadi River in the state of Orissa, India. The results obtained are compared against the results derived from the traditional Box–Jenkins approach. While the correlation coefficient between the observed and predicted streamflows was found to be 0·77 in case of SVR, the same for different auto‐regressive integrated moving average (ARIMA) models ranges between 0·67 and 0·69. The superiority of SVR as compared to traditional Box‐Jenkins approach is also explained through the feature space representation. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
90.
Suman Goyal Ashish Kumar M Mohapatra L S Rathore S K Dube Rahul Saxena R K Giri 《Journal of Earth System Science》2017,126(6):79
India experiences severe thunderstorms during the months, March–June. But these systems are not predicted well, mainly due to the absence of mesoscale observational network over Indian region and the expert system. As these are short lived systems, the nowcast is attempted worldwide based on satellite and radar observations. Due to inadequate radar network, satellite plays the dominant role for nowcast of these thunderstorms. In this study, a nowcast based algorithm ForTracc developed by Vila et al. (Weather Forecast 23:233–245, 2008) has been examined over the Indian region using Infrared Channel \((10.8~\upmu \hbox {m})\) of INSAT-3D for prediction of Mesoscale Convective Systems (MCS). In this technique, the current location and intensity in terms of Cloud Top Brightness Temperature (CTBT) of the MCS are extrapolated. The purpose of this study is to validate this satellite-based nowcasting technique for Convective Cloud Clusters that helps in optimum utilization of satellite data and improve the nowcasting. The model could predict reasonably the minimum CTBT of the convective cell with average absolute error (AAE) of \({<}7\hbox { K}\) for different lead periods (30–180 min). However, it was underestimated for all the lead periods of forecasts. The AAE in the forecasts of size of the cluster varies from about \(3\times 10^{4}\hbox { km}^{2}\) for 30-min forecast to \(7\times 10^{4}\hbox { km}^{2}\) for 120-min forecast. The mean absolute error in prediction of size is above 31–38% of actual size for different lead periods of forecasts from 30 to 180 min. There is over estimation in prediction of size for 30 and 60 min forecasts (17% and 2.6% of actual size of the cluster, respectively) and underestimation in 90 to 180-min forecasts (–2.4% to –28%). The direct position error (DPE) based on the location of minimum CTBT ranges from 70 to 144 km for 30–180-min forecast respectively. 相似文献