Hydrothermal fracture controlled vein type uranium mineralization in the Paleoproterozoic Bijawar Group of rocks,Sonrai basin,Lalitpur district,U.P. – Fresh findings from subsurface borehole data

Sonrai basin, located along the southwestern margin of Bundelkhand Granite-Gneiss Complex (BGC) is known for its base metal and phosphorite mineralization. Uranium mineralization of appreciable grade and thickness was reported in Pisnari block in the northern part of this basin during sub-surface exploration activity in 1976-97. This was in the form of uranium-bitumin association within fractures in the carbonate-terrigenous sediments of Gorakalan shale, Rohini carbonate and Bandai sandstone of Sonrai Formation of Bijawar Group. Similar mineralization was also noted within the lower chloritic shale member of Solda Formation of the same Group. During subsequent drilling activity at a later phase (2005-09), uranium rich zones within Rohini carbonate and chloritic shale members were corroborated by the interception of mineralized bands in two boreholes drilled near Pisnari. Petrographic study of radioactive core samples reveal that uranium mineralization is closely associated with globular carbonaceous matter and sulphides along the fractures. Uranium is either adsorbed in carbonaceous matter or occurs as ultrafine inclusions of coffinite within carbonaceous matter. An additional phase of secondary uranium mineral (uranophane) is also noted in one of the boreholes. The uranium minerals, in association with sulphides, fill up moderately dipping fractures (approximately 15o towards North) which are oblique to the core axis of the inclined borehole and thus, the mineralization is characterized as hydrothermal fracture-controlled vein type mineralisation. C-HN- S analysis of carbonaceous matter occurring in close association with the uranium minerals reveal heterogeneity in composition with respect to carbon and sulfur. The present paper aims at discussing the geological, petrological and radiometric aspects of this mineralization, so as to enhance the understanding of the same.     

Reliability of reanalyses products in simulating precipitation and temperature characteristics over India

Various reanalyses have been utilized in numerous climate related researches around the globe, however, there exists considerable biasedness in these products, especially in precipitation and temperature data. The ability of these reanalysis products to simulate the precipitation and temperature patterns is observed to be satisfactory at global scale, while it differs significantly at regional scale, especially over regions of high spatio-temporal heterogeneity such as India. Therefore, it is essential to evaluate the applicability and robustness of reanalyses in climate related research. The annual and seasonal variability in spatio-temporal patterns and trends of precipitation and temperature data, with respect to the IMD gridded data over 34 yrs, are evaluated for six global reanalyses namely, NCEP/NCAR Reanalysis (NCEP R1), NCEP-DOE AMIP-2 Reanalysis (NCEP R2), Climate Forecast System Reanalysis (CFSR), ECMWF Interim Reanalysis (ERA-Interim), Modern Era Retrospective Analysis for Research and Application Land only model (MERRA-Land) and JMA 55-year Reanalysis (JRA-55). The ability of the reanalyses was tested based on several factors such as statistical and categorical indices, spells and trends, for annual and seasonal daily values. Several regional and seasonal differences were observed, particularly over high rainfall regions such as Western Ghats and northeastern India. MERRA-Land is found to give the best results for precipitation over India, which is attributed to the updated forcing data using gauge-based precipitation observations. Similarly, ERA-Interim and JRA-55 exhibit better performance for temperature than other datasets. All reanalyses failed to correctly reproduce the trends in IMD data, for both precipitation and temperature. These observations will provide a better perception on the reliability and applicability of reanalyses for climate and hydrological studies over India.     

GIS professional development for teachers: lessons learned from high-needs schools

University faculty partners from the Departments of Geography and Instruction and Teacher Education at a large, public university collaborated with K-12 teachers and the leadership of a rural school district in order to investigate the crosscutting content of science, mathematics, and geography through the integration of web-based GIS technologies. The project explored the critical connections among technology, pedagogy, and content with a particular emphasis on developing technology-enhanced, inquiry-based lessons in which the teachers and their students used GIS technologies to analyze, visualize, and present data in real-world contexts. The findings highlight the importance of well-structured professional development that builds community, integrates diverse content and pedagogical expertise, provides feedback and coaching, and is of sufficient duration to effect change.     

Correction to: Effect of time and space partitioning strategies of samples on regional landslide susceptibility modelling

Landslides - A Correction to this paper has been published: https://doi.org/10.1007/s10346-021-01646-0.     

Effect of time and space partitioning strategies of samples on regional landslide susceptibility modelling

Landslides - Assessment of the spatial probability of future landslide occurrences for disaster risk reduction is done through landslide susceptibility modelling. In this study, we investigated the...     

Geospatial landslide inventory of India—an insight into occurrence and exposure on a national scale

Landslides - India ranks first in the world in terms of fatal landslides. Large vulnerable area (0.42 million km2), high population density and monsoon rainfall make India’s landslide...     

Application of soft computing techniques for shallow foundation reliability in geotechnical engineering

This research focuses on the application of three soft computing techniques including Minimax Probability Machine Regression(MPMR),Particle Swarm Optimization based Artificial Neural Network(ANN-PSO)and Particle Swarm Optimization based Adaptive Network Fuzzy Inference System(ANFIS-PSO)to study the shallow foundation reliability based on settlement criteria.Soil is a heterogeneous medium and the involvement of its attributes for geotechnical behaviour in soil-foundation system makes the prediction of settlement of shallow a complex engineering problem.This study explores the feasibility of soft computing techniques against the deterministic approach.The settlement of shallow foundation depends on the parametersγ(unit weight),e0(void ratio)and CC(compression index).These soil parameters are taken as input variables while the settlement of shallow foundation as output.To assess the performance of models,different performance indices i.e.RMSE,VAF,R^2,Bias Factor,MAPE,LMI,U(95),RSR,NS,RPD,etc.were used.From the analysis of results,it was found that MPMR model outperformed PSO-ANFIS and PSO-ANN.Therefore,MPMR can be used as a reliable soft computing technique for non-linear problems for settlement of shallow foundations on soils.     

Sea Level Rise in Miami Beach: Vulnerability and Real Estate Exposure

Sea level rise threatens coastal communities throughout the United States, and South Florida is on the front line. The iconic and built-up city of Miami Beach, Florida, has a well-developed, high-value property market, and the municipality has been lauded for proactively taking action to adapt to anticipated sea level rise. Moving beyond hyperbole and piecemeal evidence, we compile a comprehensive inventory of adaptation and mitigation measures implemented by various municipal agencies. We employ these data sets to measure exposure and readiness for the entire city and make a preliminary effort to develop a city vulnerability index. Our findings reveal that exposure throughout the city is high and that readiness is concentrated near stormwater drainage systems, leading to high vulnerability along the coast. When we compare the spatial patterns of the vulnerability index and the residential property values, we find a mismatch. The most vulnerable regions are characterized by high income, transiency, and an apparent unresponsiveness to sea level rise. No doubt our findings illustrate a lag effect, but if sea level rise increases, the real estate market could reach a tipping point unless state and federal agencies also fund more comprehensive adaptation.     

Search for H I emission from superdisk candidates associated with radio galaxies

Giant gaseous layers(termed “superdisks”) have been hypothesized in the past to account for the strip-like radio emission gap(or straight-edged central brightness depression) observed between twin radio lobes, in over a dozen relatively nearby powerful Fanaroff-Riley Class II radio galaxies. They could also provide a plausible alternative explanation for a range of observations. Although a number of explanations have been proposed for the origin of the superdisks, little is known about their material content. Some X-ray observations of superdisk candidates indicate the presence of hot gas, but a cool dusty medium also seems to be common. If they are entirely or partly composed of neutral gas, then it may be directly detectable and we report here a first attempt to detect/image any neutral hydrogen gas present in the superdisks that are inferred to be present in four nearby radio galaxies. We have not found a positive H I signal in any of the four sources, resulting in tight upper limits on the H I number density in the postulated superdisks,estimated directly from the central rms noise values of the final radio continuum subtracted image. The estimated ranges of the upper limit on neutral hydrogen number density and column density are 10^-4-10^-3 atoms per cm3 and 10^19-10^20 atoms per cm^2, respectively. No positive H I signal is detected even after combining all the four available H I images(with inverse variance weighting). This clearly rules out an H I dominated superdisk as a viable model to explain these structures, however, the possibility of a superdisk being composed of warm/hot gas still remains open.     

Patterns of carbon sequestration in forests of western ghats and study of applicability of remote sensing in generating carbon credits through afforestation/reforestation

Satellite remote sensing is a proven tool for mapping landuse patterns and estimating vegetation biomass/carbon. Present study aims at estimating the potential of forests of Radhanagari WLS (Western Ghats, India) to sequester the atmospheric carbon-di-oxide, using ground based observations coupled with satellite remote sensing. The study area was stratified for dominant forest types based on the structure and composition of vegetation and elevation variations. Permanent sample plots were laid down in these homogeneous vegetation strata (HVS) to make different observations during time 1 and time 2. Carbon sequestration by plantations was also studied and compared with natural forests. Species and area-specific biomass equations were used for estimating carbon pool and sequestration. Among natural forests ‘mixed moist deciduous’ forests exhibited highest sequestration rate (8%), whereas, plantation as obvious had a comparatively higher sequestration rate than natural forests (20.27%). Total carbon sequestration by forests of the Radhanagari WLS between 2004 and 2006 is 78742.09 tons. Eligible land for reforestation activity under clean development mechanism (CDM) of Kyoto Protocol was identified using satellite remote sensing using 1989 and 2005 datasets and it was observed that the potential land that can be used for reforestation activity is 10080 ha.