Interannual variability and predictability of sea level along the Indian Coast

Summary The Indian coast stretching more than 7,500 km constitutes the major portion of the South Asian coastline in the North Indian Ocean region. The South Asian region is significantly influenced by meteorological/oceanographic phenomena like monsoons, El Ni?o/Southern Oscillation (ENSO) and tropical cyclones. Direct/indirect impacts of these phenomena, which exhibit large interannual variabilities, on sea level changes in this region are considerable. Our results show that the mean sea level along the eastern coast of India, which is highly vulnerable to the incidence of severe tropical cyclones, is considerably higher than normal during the intense cyclonic period of a year falling in the positive phase of the Southern Oscillation (La Ni?a epoch), thereby enhancing the hazardous potential of tropical cyclones. Further, in the closing phase of the La Ni?a southwest monsoon, higher sea level anomalies prevail along the Indian coast raising the flooding potential of such monsoons. Over the west coast of India significant simultaneous correlations have been found between the amount of southwest monsoon rainfall and the mean sea level during the period from June to September. Over the east coast of India at Visakhapatnam, mean sea level is predictable with a fair degree of confidence one month in advance, by using the Sea Surface Temperature (SST) and the Southern Oscillation Index (SOI) as predictors. These results will be useful in the annual preparedness programmes aimed at mitigating the impacts of natural disasters like tropical cyclones and floods in the South Asian region. Received November 9, 2001     

Ensemble clustering for efficient robust optimization of naturally fractured reservoirs

In the development of naturally fractured reservoirs (NFRs), the existence of natural fractures induces severe fingering and breakthrough. To manage the flooding process and improve the ultimate recovery, we propose a numerical workflow to generate optimal production schedules for smart wells, in which the inflow control valve (ICV) settings can be controlled individually. To properly consider the uncertainty introduced by randomly distributed natural fractures, the robust optimization would require a large ensemble size and it would be computationally demanding. In this work, a hierarchical clustering method is proposed to select representative models for the robust optimization in order to avoid redundant simulation runs and improve the efficiency of the robust optimization. By reducing the full ensemble of models into a small subset ensemble, the efficiency of the robust optimization algorithm is significantly improved. The robust optimization is performed using the StoSAG scheme to find the optimal well controls that maximize the net-present-value (NPV) of the NFR’s development. Due to the discrete property of a natural fracture field, traditional feature extraction methods such as model-parameter-based clustering may not be directly applicable. Therefore, two different kinds of clustering-based optimization methods, a state-based (e.g., s _w profiles) clustering and a response-based (e.g., production rates) clustering, are proposed and compared. The computational results show that the robust clustering optimization could increase the computational efficiency significantly without sacrificing much expected NPV of the robust optimization. Moreover, the performance of different clustering algorithms varies widely in correspondence to different selections of clustering features. By properly extracting model features, the clustered subset could adequately represent the uncertainty of the full ensemble.     

Progress in China’s sustainable development research: Contribution of Chinese geographers

Sustainable development has always been a hotspot in Chinese geographical research. Herein, we conduct a systematic statistical analysis of the contribution of Chinese geographers to sustainable development research using bibliometric methods. Based on the review of a vast amount of literature, we identify the main research teams, research funding sources, journals, and key research fields. The findings are as follows: (1) the resources and environmental institutes of the Chinese Academy of Sciences have a significant influence on sustainable development research; (2) China’s central government foundations (the National Natural Science Foundation of China and National Social Sciences Fund) are the main research funding sources; (3) most of the highly cited articles are published in journals sponsored by the Geographical Society of China; and (4) sustainable development theory and its research areas are being constantly enriched and perfected. Based on the statistics of keywords, the theory, research methods, research regional scales, and key research areas are summarized and expounded.     

Sensitivity of Mesoscale Model Forecast During a Satellite Launch to Different Cumulus Parameterization Schemes in MM5

The identification of the model discrepancy and skill is crucial when a forecast is issued. The characterization of the model errors for different cumulus parameterization schemes (CPSs) provides more confidence on the model outputs and qualifies which CPSs are to be used for better forecasts. Cases of good/bad skill scores can be isolated and clustered into weather systems to identify the atmospheric structures that cause difficulties to the forecasts. The objective of this work is to study the sensitivity of weather forecast, produced using the PSU-NCAR Mesoscale Model version 5 (MM5) during the launch of an Indian satellite on 5th May, 2005, to the way in which convective processes are parameterized in the model. The real-time MM5 simulations were made for providing the weather conditions near the launch station Sriharikota (SHAR). A total of 10 simulations (each of 48 h) for the period 25th April to 04th May, 2005 over the Indian region and surrounding oceans were made using different CPSs. The 24 h and 48 h model predicted wind, temperature and moisture fields for different CPSs, namely the Kuo, Grell, Kain-Fritsch and Betts-Miller, are statistically evaluated by calculating parameters such as mean bias, root-mean-squares error (RMSE), and correlation coefficients by comparison with radiosonde observation. The performance of the different CPSs, in simulating the area of rainfall is evaluated by calculating bias scores (BSs) and equitable threat scores (ETSs). In order to compute BSs and ETSs the model predicted rainfall is compared with Tropical Rainfall Measuring Mission (TRMM) observed rainfall. It was observed that model simulated wind and temperature fields by all the CPSs are in reasonable agreement with that of radiosonde observation. The RMSE of wind speed, temperature and relative humidity do not show significant differences among the four CPSs. Temperature and relative humidity were overestimated by all the CPSs, while wind speed is underestimated, except in the upper levels. The model predicted moisture fields by all CPSs show substantial disagreement when compared with observation. Grell scheme outperforms the other CPSs in simulating wind speed, temperature and relative humidity, particularly in the upper levels, which implies that representing entrainment/detrainment in the cloud column may not necessarily be a beneficial assumption in tropical atmospheres. It is observed that MM5 overestimates the area of light precipitation, while the area of heavy precipitation is underestimated. The least predictive skill shown by Kuo for light and moderate precipitation asserts that this scheme is more suitable for larger grid scale (>30 km). In the predictive skill for the area of light precipitation the Betts-Miller scheme has a clear edge over the other CPSs. The evaluation of the MM5 model for different CPSs conducted during this study is only for a particular synoptic situation. More detailed studies however, are required to assess the forecast skill of the CPSs for different synoptic situations.     

Evaluation of Subsurface Lithologic Units for Groundwater Exploration in the Barind Tract of Bangladesh

Barind Tract, located north western part of Bangladesh, is one of the most diversified physiographic units of the country. The surface water supply in this part is particularly limited, so the irrigation is almost entirely depends on groundwater. However, over exploitation indicates falling groundwater heads in this area. The objective of present study is to examine the nature of the aquifer system Barind Tract of Bangladesh in order to assess the sustainability of groundwater yield. Borehole lithology data were collected, processed and analyzed for this purpose. Representative panel diagram, 3-D stratigraphic and cross-sectional views were also prepared for necessary assessment of the variation of individual subsurface stratum in different locations. The study identified three subsurface geologic formations namely, a top clay layer, sand layer of different grain size and at the bottom an impermeable clay zone. Maps of formation thickness and index revealed that aquifer thickness is low in the north-western corner and in some places of middle of south-western corner. The thickness of sand formation in other places is recorded above 20 m. It is expect that the finding of the study will help groundwater resources development, planning and management in the area.     

Heavy metal contamination of cultivated wetland soils along a typical plateau lake from southwest China

Topsoil (0–20 cm) samples were collected from four cultivated wetlands including Northern and Western Fields (about 30-year tillage), and Southern and Western Fields (about 20-year tillage) along the Yilong Lake of China in October, 2005. Total concentrations of As, Cr, Cu, Pb, and Zn were determined using the inductively coupled plasma atomic absorption spectrometry in order to assess contamination status in four sampling plots. Results showed that the average concentrations of these heavy metals in Northern and Western Fields were significantly (P < 0.01) higher than those in reference soils, while they were generally lower in Southern and Eastern Fields. All the mean concentrations of heavy metals were lower, except that the average concentrations of As and Cr in Northern Field slightly exceeded the soil quality guidelines. The contamination indices showed low-contamination levels for As, Cu, Pb, and Zn in Northern and Western Fields, while no contamination levels could be observed in Southern and Eastern Fields. As for Cr, they showed moderate-contamination levels in Northern Field, but low or no contamination levels in other three Fields. The integrated contamination index values indicated Northern and Western Fields were moderately contaminated, while Southern and Eastern Fields were less contaminated. The same contamination sources of these heavy metals were identified in these fields using factor- and cluster analysis.     

The polar form of the spherical harmonic spectrum: implications for filtering <Emphasis Type="BoldSmallCaps">grace</Emphasis> data

Representing the spherical harmonic spectrum of a field on the sphere in terms of its amplitude and phase is termed as its polar form. In this study, we look at how the amplitude and phase are affected by linear low-pass filtering. The impact of filtering on amplitude is well understood, but that on phase has not been studied previously. Here, we demonstrate that a certain class of filters only affect the amplitude of the spherical harmonic spectrum and not the phase, but the others affect both the amplitude and phase. Further, we also demonstrate that the filtered phase helps in ascertaining the efficacy of decorrelation filters used in the grace community.     

Effect of heat treatment on dynamic properties of selected rock types taken from the Salt Range in Pakistan

Temperature is one of the variables that influence the elasto-plastic behavior and integrity of rock outcrops. Fluctuations in temperature can trigger alteration of some of the mineral properties and impact the brittle-plastic transition. Initiation and propagation of thermally induced tension cracks tend to weaken most rock types. The principal goal of this study was to anticipate impacts of thermal stress-strain cycles on the dynamic response of representative rock units exposed in the Khewra Gorge of the Salt Range Punjab of Pakistan. Ten types of sedimentary rock units were sampled, including marl, dolomite, three types of limestone, and five different sandstones exhibiting varying characteristics in outcrop. Boulder specimens were collected from the field and transported to the laboratory to prepare 50 drill cores that could be subjected to thermal cycling between 50 and 200 °C in increments of 50 °C. Room temperature core samples were tested using an Erudite resonance frequency meter to measure their Q-factors and the resonance frequency (F_r) at an applied loading frequency of 7 KHz with 0.01 V output voltage. Results suggest that thermal cycling tends to reduce the dynamic Young’s modulus (E_d) and Q-factor. Other parameters, such as damping ratio (ξ), specific damping capacity (Ψ), and loss factor (?) appeared to increase with increasing temperature cycles, likely as a result of developing thermally induced tensile fractures. The resultant values of the null hypothesis (t-critical and t-stats) suggests that the null hypothesis can be discarded because there was no observable difference between the measured and expected values for the cores tested. The observations and data emanating from this study might be useful in designing low-level radioactive waste landfills, nuclear waste repositories, and deep underground excavations where the increased temperature could alter the mechanical behavior of the parent rock mass.     

Assessment of the reliability of supervised classifications of Landsat-7, ASTER,and SPOT-5 multispectral data in rock unit discriminations of Jabal Daf-Wadi Fatima area,Saudi Arabia

Multispectral, multiresolution remotely sensed data were processed to emphasize geological interpretation of Jabal Daf-Wadi Fatima area. The investigated area is situated in the central western part of Saudi Arabia and geologically consists of igneous and metamorphosed rocks overlain by sedimentary sequence belonging to the Arabian-Nubian Shield. Three sets of digital satellite data, Landsat-7 ETM+, ASTER, and SPOT-5, were used in this study. The application of image processing techniques enables to identify and delineate the lithologic units and the structural features of the study area. The results of this study indicate that the confusion matrix of the three maximum likelihood supervised classifications of the three datasets shows that the Landsat ETM+ bands scored the best degree of average and overall accuracy (77 and 78%, respectively). This classification distinguishes most of the rock units for mapping in the investigated area. The supervised classification of ASTER and SPOT bands has lower degrees of accuracy than the classified Landsat data. The supervised classification of SPOT bands has a degree of average and overall accuracy of 66 and 67%, respectively, but it is the best for distinguishing the spectral signatures of the different members of Fatima Formation (lower, middle, and upper members). The statistical analyses of the confusion matrices of classifications and the interpretation of the produced classified thematic maps revealed that the classification accuracy does not necessary depend on the spatial resolution of satellite data. The data of the highest spatial resolution such as SPOT data are also very useful in emphasizing and classifying the rock units of a small outcrop area. The detailed geological map of Jabal Daf-Wadi Fatima area is interpreted in this work from supervised classified images of different resolutions as well as the structure map of this area. This study shows that it is preferable to use the supervised classifications of multiresolution data for rock unit discrimination in detailed field mapping.     

Structural properties of Urfa stone doped with erbium oxide

In this study, we investigated the structural properties of Urfa stone (US) doped with erbium oxide (Er₂O₃). Solid US was powdered by using an agate mortar, and its elemental composition was determined using inductive coupling plasma (ICP) methods. Varying amounts of Er₂O₃ (5, 10, 20, 30, and 40%) were added as a dopant to the US powder using mechanical alloying methods. The resultant samples were sintered at 1000 °C for 1 h. The structural properties of the Er₂O₃-doped US samples were subsequently investigated using X-ray diffraction (XRD), Fourier-transform infrared spectrometry (FTIR), and photoluminescence methods. Results from the XRD analysis of the Er₂O₃-doped US powder indicated two crystalline phases: (1) calcium oxide (CaO) or lime and (2) Er₂O₃. After the samples were sintered at 1000 °C, CaO, Er₂O₃, calcium carbonate (CaCO₃), and mixed crystalline phases were observed. Results from the FTIR analysis of the Er₂O₃-doped US samples indicated absorption bands at 711.91, 872.08, and 1396.87 cm^?1 in the spectra. Finally, photoluminescence analysis results indicated a shift in the emission and excitation bands to longer and shorter wavelengths, respectively, in the solid state (non-aqueous media) US-Er complex.