Shallow seismicity, stress distribution and crustal deformation pattern in the Andaman-West Sunda arc and Andaman Sea, northeastern Indian Ocean

Shallow seismicity and available source mechanisms in the Andaman–westSunda arc and Andaman sea region suggest distinct variation in stressdistribution pattern both along and across the arc in the overriding plate.Seismotectonic regionalisation indicates that the region could be dividedinto eight broad seismogenic sources of relatively homogeneousdeformation. Crustal deformation rates have been determined for each oneof these sources based on the summation of moment tensors. The analysisshowed that the entire fore arc region is dominated by compressive stresseswith compression in a mean direction of N23^°, and the rates ofseismic deformation velocities in this belt decrease northward from 5.2± 0.65 mm/yr near Nias island off Sumatra and 1.12 ±0.13 mm/yr near Great Nicobar islands to as much as 0.4 ±0.04 mm/yr north of 8^°N along Andaman–Nicobar islandsregion. The deformation velocities indicate, extension of 0.83 ±0.05 mm/yr along N343^° and compression of 0.19 ±0.01 mm/yr along N73^° in the Andaman back arc spreadingregion, extension of 0.18 ± 0.01 mm/yr along N125^° andcompression of 0.16 ± 0.01 mm/yr along N35^° in NicobarDeep and west Andaman fault zone, compression of 0.84 ±0.12 mm/yr N341^° and extension of 0.77 ± 0.11 mm/yralong N72^° within the transverse tectonic zone in the Andamantrench, N-S compression of 3.19 ± 0.29 mm/yr and an E-Wextension of 1.24 ± 0.11 mm/yr in the Semangko fault zone ofnorth Sumatra. The vertical deformation suggests crustal thinning in theAndaman sea and crustal thickening in the fore arc and Semangko faultzones. The apparent stresses calculated for all major events range between0.1–10 bars and the values increase with increasing seismic moment.However, the apparent stress estimates neither indicate any significantvariation with faulting type nor display any variation across the arc, incontrast to the general observation that the fore arc thrust events showhigher stress levels in the shallow subduction zones. It is inferred that theoblique plate convergence, partial subduction of 90^°E Ridge innorth below the Andaman trench and the active back arc spreading are themain contributing factors for the observed stress field within the overridingplate in this region.     

Dleineation and characterization of geomorphological features in a part of lower maharahstra metamorphic plateau using IRS-ID LISS-III Data

In the present study, an attempt has been made to delineate and characterize the different geomorphic units of Tundiya river catchment in a part of Lower Maharahstra Metamorphic Plateau, north-eastern part of Nagpur district, Maharashtra. The drainage, contour and delineated geological units have been overlaid on IRS-ID LISS III satellite imagery (bands 2,3 and 4) in EASI/PACE analysis system to delineate and characterize different geomorphological units and analysis of their processes based on the field observations. The study area is basically of metamorphic in origin with different geological formations and is influenced by the various fluvio-morphological processes. Based on the satellite data analysis, the distinct geomorphological units viz., table top summits, structural hills, subdued plateau, linear ridges, shallow, moderate and deeply buried foot slopes, shallow valley fills and deep valley fills have been delineated and characterized. The information generated from satellite data in the form of vector layers has been used in GIS to generate geological and geomorphological maps of the study area. The present study demonstrates that IRS-ID LISS-III data in conjunction with geology, drainage and contour parameters to enable detailed evaluation of different geomorphological units and analysis of their processes based on the field observations. The delineated geomorphological units can be utilized for evaluation and management of natural resources and geo-environment on sustainable basis at river catchment level.     

Remote sensing and gis applications in the identification of aquaculture hotspots at village level

Interpretation of IRS LISS II and LISS III imagery has revealed the various landforms as well as land use/land cover features in a part of the Godavari delta coastal belt. A comparative analysis of geomorphological vs. land use/land cover maps suggested that the landforms exert a certain degree of control over human land use activities even in this monotonously plain area. Further, an analysis of the sequential imagery pertaining to 1992 and 2001 aimed at detecting the land use/land cover change has indicated that the aquaculture has phenomenally increased by 9,293.5 ha during the 9-year period. At the same time, the cropland which occupied about 29,104 ha in 1992 has been reduced to 19,153.9 ha by 2001 mainly due to the encroachment of aquaculture. Village level data on temporal variation in land use/land cover extracted through GIS analysis revealed that in 14 out of the total 39 villages in the area, the conversion of cropland into aquaculture ponds was more than 30% with the highest conversion rate of 89.8% in Gondi village. These fourteen villages, which are designated as ‘aquaculture hotspots’ are grouped into 4 priority classes based on the intensity of conversion.     

Electrokinetic remediation of metal contaminated glacial tills

This paper presents the results of an experimental investigation which studied the feasibility of using the electrokinetic process to remediate contaminated clays of glacial origin, otherwise known as glacial tills. An overview of the electrokinetic phenomena, as well as previously performed laboratory and field investigations, is first presented. The methodology of the electrokinetic experiments which were conducted to investigate the removal of metals from a glacial till is then described. A total of 16 experiments were conducted using glacial till samples obtained from a project site near Chicago. Sodium and calcium were used as the surrogate cationic metallic contaminants. These experiments demonstrated that ion transport during the electrokinetic process occurs due to both electro-osmosis and electromigration, but that due to electromigration is significantly higher than that due to electro-osmosis. Unlike other clays such as kaolinite, the glacial till used for this investigation possessed high buffering capacity because of its high carbonate content which prevented the acid front migration from the anode to the cathode during the electrokinetic process. The ion removal efficiency of the electrokinetic process was found to increase when: (1) the voltage gradient applied to the soil was increased, (2) the initial concentration of the contaminants was increased, and (3) the duration of the treatment process was increased. The ion removal efficiency was also greater for smaller ions which possess less ionic charge and when the ions existed independently in the soil as compared to when they coexisted. This investigation suggests that the electrokinetic process has significant potential for remediating glacial tills contaminated with metals. However, the properties of Na and Ca are not representative of contaminants, such as heavy metals, so further investigations are needed.     

Ensemble prediction of regional droughts using climate inputs and the SVM–copula approach

In this study, the climate teleconnections with meteorological droughts are analysed and used to develop ensemble drought prediction models using a support vector machine (SVM)–copula approach over Western Rajasthan (India). The meteorological droughts are identified using the Standardized Precipitation Index (SPI). In the analysis of large‐scale climate forcing represented by climate indices such as El Niño Southern Oscillation, Indian Ocean Dipole Mode and Atlantic Multidecadal Oscillation on regional droughts, it is found that regional droughts exhibits interannual as well as interdecadal variability. On the basis of potential teleconnections between regional droughts and climate indices, SPI‐based drought forecasting models are developed with up to 3 months' lead time. As traditional statistical forecast models are unable to capture nonlinearity and nonstationarity associated with drought forecasts, a machine learning technique, namely, support vector regression (SVR), is adopted to forecast the drought index, and the copula method is used to model the joint distribution of observed and predicted drought index. The copula‐based conditional distribution of an observed drought index conditioned on predicted drought index is utilized to simulate ensembles of drought forecasts. Two variants of drought forecast models are developed, namely a single model for all the periods in a year and separate models for each of the four seasons in a year. The performance of developed models is validated for predicting drought time series for 10 years' data. Improvement in ensemble prediction of drought indices is observed for combined seasonal model over the single model without seasonal partitions. The results show that the proposed SVM–copula approach improves the drought prediction capability and provides estimation of uncertainty associated with drought predictions. Copyright © 2013 John Wiley & Sons, Ltd.