Escalation of salinity levels in the quaternary aquifers of the Ganga alluvial plain,India

A detailed water quality analysis was carried out in the quaternary aquifer system of the marginal alluvial plain (Ganga Plain) in Bah Tahsil, Agra district, India. The electrical conductivity of 50 samples each from dug wells, hand pumps and tube wells was analysed for the study of salinity levels in shallow, intermediate and deep aquifers. Out of 50, 20 samples of each were also analysed for other chemical constituents such as Na⁺, K⁺, Cl⁻, F⁻ and TDS. The analyses show drastic changes in the salinity levels of shallow, intermediate and deep aquifers. The deep aquifers are more saline compared to the shallow and intermediate aquifers. On the contrary, the concentration of chemical constituents such as Na⁺, K⁺, Cl⁻ and F⁻ was more in the shallow aquifers compared to the deep aquifers. Moreover, there is an indication that the salinity and concentration of the above chemical constituents also escalate with time in each aquifer. The chemical constituents such as Na⁺, K⁺, Cl⁻, F⁻ and TDS range from 51 to 165 mg/l, 1 to 14 mg/l, 224 to 1,459 mg/l, 0 to 1.5 mg/l and 750 to 2,650 mg/l, respectively. Over a 3-year period, the salinity levels have sharply increased and the average F level has increased by 0.1–0.3 mg/l. An attempt has been made here to discuss the factors causing the variation and escalation of chemical constituents and salinity in the water of the three aquifers.     

New statistical models for long-range forecasting of southwest monsoon rainfall over India

The India Meteorological Department (IMD) has been issuing long-range forecasts (LRF) based on statistical methods for the southwest monsoon rainfall over India (ISMR) for more than 100 years. Many statistical and dynamical models including the operational models of IMD failed to predict the recent deficient monsoon years of 2002 and 2004. In this paper, we report the improved results of new experimental statistical models developed for LRF of southwest monsoon seasonal (June–September) rainfall. These models were developed to facilitate the IMD’s present two-stage operational forecast strategy. Models based on the ensemble multiple linear regression (EMR) and projection pursuit regression (PPR) techniques were developed to forecast the ISMR. These models used new methods of predictor selection and model development. After carrying out a detailed analysis of various global climate data sets; two predictor sets, each consisting of six predictors were selected. Our model performance was evaluated for the period from 1981 to 2004 by sliding the model training period with a window length of 23 years. The new models showed better performance in their hindcast, compared to the model based on climatology. The Heidke scores for the three category forecasts during the verification period by the first stage models based on EMR and PPR methods were 0.5 and 0.44, respectively, and those of June models were 0.63 and 0.38, respectively. Root mean square error of these models during the verification period (1981–2004) varied between 4.56 and 6.75% from long period average (LPA) as against 10.0% from the LPA of the model based on climatology alone. These models were able to provide correct forecasts of the recent two deficient monsoon rainfall events (2002 and 2004). The experimental forecasts for the 2005 southwest monsoon season based on these models were also found to be accurate.     

Field Survey of Tsunami Effects in Sri Lanka due to the Sumatra-Andaman Earthquake of December 26, 2004

The December 26, 2004 Sumatra-Andaman earthquake that registered a moment magnitude (M_w) of 9.1 was one of the largest earthquakes in the world since 1900. The devastating tsunami that resulted from this earthquake caused more casualties than any previously reported tsunami. The number of fatalities and missing persons in the most seriously affected countries were Indonesia - 167,736, Sri Lanka - 35,322, India - 18,045 and Thailand - 8,212. This paper describes two field visits to assess tsunami effects in Sri Lanka by a combined team of Japanese and Sri Lankan researchers. The first field visit from December 30, 2004 – January 04, 2005 covered the western and southern coasts of Sri Lanka including the cities of Moratuwa, Beruwala, Bentota, Pereliya, Hikkaduwa, Galle, Talpe, Matara, Tangalla and Hambantota. The objectives of the first field visit were to investigate the damage caused by the tsunami and to obtain eyewitness information about wave arrival times. The second field visit from March 10–18, 2005 covered the eastern and southern coasts of Sri Lanka and included Trincomalee, Batticaloa, Arugam Bay, Yala National Park and Kirinda. The objectives of the second visit were mainly to obtain eyewitness information about wave arrival times and inundation data, and to take relevant measurements using GPS instruments.     

Bianchi Type I Anisotropic Magnetized Cosmological Model in General Relativity

Bianchi Type I magnetized Cosmological model for perfect fluid distribution is investigated. The magnetic field is due to an electric current produced along x-axis. The distribution consists of an electrically neutral perfect fluid with an infinite electrical conductivity. To get a determinate solution, a supplementary conditionA = BC between metric potentials is used. The behaviour of the model in presence and absence of magnetic field is also discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

Comparative study of neural network,fuzzy logic and linear transfer function techniques in daily rainfall‐runoff modelling under different input domains

This paper compares artificial neural network (ANN), fuzzy logic (FL) and linear transfer function (LTF)‐based approaches for daily rainfall‐runoff modelling. This study also investigates the potential of Takagi‐Sugeno (TS) fuzzy model and the impact of antecedent soil moisture conditions in the performance of the daily rainfall‐runoff models. Eleven different input vectors under four classes, i.e. (i) rainfall, (ii) rainfall and antecedent moisture content, (iii) rainfall and runoff and (iv) rainfall, runoff and antecedent moisture content are considered for examining the effects of input data vector on rainfall‐runoff modelling. Using the rainfall‐runoff data of the upper Narmada basin, Central India, a suitable modelling technique with appropriate model input structure is suggested on the basis of various model performance indices. The results show that the fuzzy modelling approach is uniformly outperforming the LTF and also always superior to the ANN‐based models. Copyright © 2010 John Wiley & Sons, Ltd.     

Simulations of Cyclone Sidr in the Bay of Bengal with a high-resolution model: sensitivity to large-scale boundary forcing

The predictability of Cyclone Sidr in the Bay of Bengal was explored in terms of track and intensity using the Advanced Research Hurricane Weather Research Forecast (AHW) model. This constitutes the first application of the AHW over an area that lies outside the region of the North Atlantic for which this model was developed and tested. Several experiments were conducted to understand the possible contributing factors that affected Sidr??s intensity and track simulation by varying the initial start time and domain size. Results show that Sidr??s track was strongly controlled by the synoptic flow at the 500-hPa level, seen especially due to the strong mid-latitude westerly over north-central India. A 96-h forecast produced westerly winds over north-central India at the 500-hPa level that were notably weaker; this likely caused the modeled cyclone track to drift from the observed actual track. Reducing the model domain size reduced model error in the synoptic-scale winds at 500?hPa and produced an improved cyclone track. Specifically, the cyclone track appeared to be sensitive to the upstream synoptic flow, and was, therefore, sensitive to the location of the western boundary of the domain. However, cyclone intensity remained largely unaffected by this synoptic wind error at the 500-hPa level. Comparison of the high resolution, moving nested domain with a single coarser resolution domain showed little difference in tracks, but resulted in significantly different intensities. Experiments on the domain size with regard to the total precipitation simulated by the model showed that precipitation patterns and 10-m surface winds were also different. This was mainly due to the mid-latitude westerly flow across the west side of the model domain. The analysis also suggested that the total precipitation pattern and track was unchanged when the domain was extended toward the east, north, and south. Furthermore, this highlights our conclusion that Sidr was influenced from the west side of the domain. The displacement error was significantly reduced after the domain size from the western model boundary was decreased. Study results demonstrate the capability and need of a high-resolution mesoscale modeling framework for simulating the complex interactions that contribute to the formation of tropical cyclones over the Bay of Bengal region.     

Atom‐probe analyses of nanodiamonds from Allende

Atom‐probe tomography (APT) is currently the only analytical technique that, due to its spatial resolution and detection efficiency, has the potential to measure the carbon isotope ratios of individual nanodiamonds. We describe three different sample preparation protocols that we developed for the APT analysis of meteoritic nanodiamonds at sub‐nm resolution and present carbon isotope peak ratios of meteoritic and synthetic nanodiamonds. The results demonstrate an instrumental bias associated with APT that needs to be quantified and corrected to obtain accurate isotope ratios. After this correction is applied, this technique should allow determination of the distribution of ¹²C/¹³C ratios in individual diamond grains, solving the decades‐old question of the origin of meteoritic nanodiamonds: what fraction, if any, formed in the solar system and in presolar environments? Furthermore, APT could help us identify the stellar sources of any presolar nanodiamonds that are detected.