Effect of Compressive Load on Oblique Pull-out Capacity of Model Piles in Sand

Model tests on steel piles embedded in sand were carried out in the laboratory to study the effects of compressive load (i.e. 0, 25, 50, 75, and 100% of their ultimate capacity in compression) on oblique pull-out capacity of piles. The model piles were of 20 mm × 20 mm cross section, which had an embedded length of 400 and 600 mm. The pull was applied at an inclination of 0°, 30°, 60° and 90° with vertical axis of the piles. The experimental results indicate that the net oblique pull-out capacity of piles decreases with increase in % of compressive load and the decrease depends on the magnitude of the compressive load. Semi-empirical methods, based on experimental results, have been suggested to determine the oblique pull-out resistance of piles subjected to static compressive loads. A comparison of predicted values of the ultimate oblique resistance by proposed methods of analysis with experimental values, and also with those reported by others, showed reasonably good agreement.     

Assessment of the groundwater potential and quality in Bhatsa and Kalu river basins of Thane district, western Deccan Volcanic Province of India

Scarcity of groundwater necessitates the present study to evaluate groundwater potential and quality for designing suitable water management plans in the Bhatsa and Kalu river basins in the Thane district in the western Deccan volcanic province of India. A Geographical Information System platform is used to integrate and spatially analyse multiparametric data comprised of satellite, topographical, geological and hydrogeological information to generate several thematic maps, including groundwater potential zonation map. This study reveals that 70% of the area has medium to low groundwater potential, while only 10% has high potential. The static and dynamic groundwater potentials are estimated to be 10.7 and 4.8% of the annual rainfall. The groundwater quality in terms of hardness, total dissolved solids, salinity and chloride is suitable for domestic and irrigational purposes. A database is developed for sustainable water management program for the region and areas where suitable water conservation techniques need to be adopted are identified.     

Gravity Field and Subsurface Geometry of the Kalpatta Granite, South India and the Tectonic Significance

The Kalpatta granite, of Pan-African age occurs in the southern granulite terrain of Peninsular India. Bouguer anomaly map of the Kalpatta and adjoining areas reveals a gravity low of 8–10 mGal centered over the Kalpatta granite and a minor low of 4–6 mGal over the adjacent Ambalavayal granite pluton. The residual anomaly map prepared for the Kalpatta granite has been utilized to obtain depth extent and 3-D geometry of the pluton. The analysis suggests that the Kalpatta granite is an elliptical and somewhat pear shaped body with horizontal dimensions of 6–11 km and extending to a depth of 6.5km, has steeply inward dipping contacts and the shape seen on the surface continues throughout its depth. The smooth oval shape could indicate low ductility contrast, deeper level of emplacement and permissive nature of the pluton. The 3-D depth model indicates an oblique section with much deeper levels exposed in the south, in other words, the crustal block encompassing the pluton has suffered a NNW tilt during uplift after the emplacement. It is further inferred that there was no post intrusive shape modification, the NW tilting of the region and denudation gave rise to the present outcrop pattern of the body.     

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.     

Evaluation of indicators for desertification risk assessment in part of Thar Desert Region of Rajasthan using geospatial techniques

Desertification has emerged as a major economic, social and environmental problem in the western part of India. The best way of dealing with desertification is to take appropriate measures to arrest land degradation, especially in areas prone to desertification. This requires an early warning system for desertification based on scientific inputs. Hence, in the present study, an attempt has been made to develop a comprehensive model for the assessment of desertification risk in the Jodhpur district of Rajasthan, India, using 23 desertification indicators. Indicators including soil, climate, vegetation and socio-economic parameters were integrated into a GIS environment to get environmental sensitive areas (ESAs) to desertification. Desertification risk index (DRI) was calculated based on ESAs to desertification, the degree of land degradation and significant desertification indicators obtained from the stepwise multiple regression model. DRI was validated by using independent indicators such as soil organic matter content and cation exchange capacity. Multiple regression analysis shows that 16 indicators out of 23 were found to be significant for assessing desertification risk at a 99% confidence interval with \(R^{2}=0.83\). The proposed methodology provides a series of effective indicators that would help to identify where desertification is a current or potential problem, and what could be the actions to alleviate the problem over time.     

Lead isotopic ratios in source apportionment of heavy metals in the street dust of Kolkata,India

Street dust from 29 locations, in some of the busiest parts of north and south Kolkata, was analysed for heavy metal composition. The decreasing order of average metal concentrations (mg kg^?1) found was Mn (390) > Pb (380) > Zn (300) > As (96) > Cu (61) > Cr (40) > Co (13) > Ag (2.1). The heavy metal composition of the Kolkata dust was compared with reported data for other cities. Enrichment factors of Pb and As were high. Multivariate statistical analysis of the heavy metals and analysis of lead isotopic ratios of the dust revealed a predominant anthropogenic influence in the contamination. The range of lead isotopic ratios found in the dust was between 0.8789 and 0.8998 with a mean Pb concentration of 383 mg kg^?1. The three Pb isotope plots of street dust, diesel and rainwater clustered linearly, while coal did not fit into this trend. The highest 207/206 lead isotopic ratio obtained was from diesel with a mean value of 0.9015, followed by the rainwater sample. The application of the binary mixing model showed that about 66.86% of lead contamination in the street dust was sourced from the atmosphere. The two components extracted by the principal component analysis explained 64.34% of the total variance. Vehicular and industrial emissions appeared to be an important contributor to the accumulation of heavy metals in the dust. The health risk assessment study of the dust indicated carcinogenic risk associated with As and Cr.     

Hyperspectral satellite data analysis for pure pixels extraction and evaluation of advanced classifier algorithms for LULC classification

The study was carried out for Indian capital city Delhi using Hyperion sensor onboard EO-1 satellite of NASA. After MODTRAN-4 based atmospheric correction, MNF, PPI and n-D visualizer were applied and endmembers of 11 LCLU classes were derived which were employed in classification of LULC. To incur better classification accuracy, a comparative study was also carried out to evaluate the potential of three classifier algorithms namely Random Forest (RF), Support Vector Machines (SVM) and Spectral Angle Mapper (SAM). The results of this study reemphasize the utility of satellite borne hyperspectral data to extract endmembers and also to delineate the potential of random forest as expert classifier to assess land cover with higher classification accuracy that outperformed the SVM by 19% and SAM by 27% in overall accuracy. This research work contributes positively to the issue of land cover classification through exploration of hyperspectral endmembers. The comparison of classification algorithms’ performance is valuable for decision makers to choose better classifier for more accurate information extraction.     

Spatio-temporal patterns of agricultural expansion and its effect on watershed degradation: a case from the mountains of Nepal

Expansion of agricultural at the cost of forested land is a common cause of watershed degradation in the mountain zones of developing countries. Many studies have been conducted to demonstrate land use changes in such regions. However, current knowledge regarding the changes, driving forces and implications of such change within the context of watershed development is limited. This study analyses changes in spatial patterns of agricultural land use and their consequences for watershed degradation during the 1976–2000 period along an altitude gradient in a watershed in Nepal, by means of remote sensing, GIS and the universal soil loss equation. Estimated soil loss ranged from 589 to 620 t ha⁻¹ y⁻¹, while areas of extreme hazard severity (>100 t ha⁻¹) increased from 9 to 14.5% from 1990 to 2000. Spatial distribution of soil loss in 2000 was characterized by 88% of total soil losses being from upland agricultural areas. The study determined that without considering other forms of land degradation, only water erosion was responsible for erosion of a substantial area in a short timeframe. Areas under upland cultivation are in an extremely vulnerable state, with these areas potentially no longer cultivable within a period of 6 years. As sustainability of the watershed is dependent on forests, continued depletion of forest resources will result in poor economic returns from agriculture for local people, together with loss of ecosystem services. Thus, in order to achieve the goal of watershed development, remaining forest lands must be kept under strict protection.