On the formation of Jupiter

Arguments are presented to show that Jupiter could not have been formed as a star of mass 0.001M and that the observed excess energy is not due to gravitational contraction from an extended, gaseous state.     

Analysis of Y-component of Geomagnetic Field and SYM-H Index Using Wavelet Multiresolution Analysis

Geomagnetism and Aeronomy - Electrodynamical coupling between the solar wind’s plasma and the Earth’s magnetosphere creates geomagnetic disturbances recorded on the ground. This work...     

Constraining probabilistic chloride mass-balance recharge estimates using baseflow and remotely sensed evapotranspiration: the Cambrian Limestone Aquifer in northern Australia

Hydrogeology Journal - Regional-scale estimates of groundwater recharge are inherently uncertain, but this uncertainty is rarely quantified. Quantifying this uncertainty provides an understanding...     

DInSAR-based monitoring of land subsidence related to groundwater over-exploitation: example from developing urban center of Nairobi,Kenya

Over-exploitation of groundwater in many evolving urban settings causes ground subsidence and permanent loss of aquifer storage capacity. DInSAR (differential interferometric synthetic aperture radar) time series data from 2016 to 2019 were used to monitor and model the surface deformation around Nairobi, Kenya, where the water demand has exceeded the supply without capacity augmentation for over two decades. The aquifer system constitutes hard rock to semiconfined ash beds in volcanic terrain. The Small Baseline DInSAR technique identified the spatial pattern of subsidence and magnitude (line-of-sight (LOS) velocity), which exceeds 41 mm/year in the semiconfined aquifer towards the western-central part of Nairobi. The spatial distribution of subsidence is consistent with the groundwater level drop and probable compaction modeled using aquifer characteristics for 1950–2015. The Global Navigation Satellite System (GNSS) data at a station from 2007 to 2018 indicate a cumulative 4-cm subsidence which is comparable to ~2.5-cm LOS subsidence from the present study for 2016–2019. The correlation with other hydrological data suggests the aquifer is experiencing inelastic subsidence due to unsustainable groundwater extraction, putting a massive strain on Nairobi’s aquifer system. The present DInSAR based study establishes its effectiveness in the monitoring of groundwater over-exploitation-based subsidence and associated hazard to the aquifer in emerging urban centers.

     

Shoreline Change Analysis at Chilika Lagoon Coast,India Using Digital Shoreline Analysis System

Shoreline is the dynamic interfaces of both terrestrial and marine environment, which constantly affected by natural coastal processes includes wave, tide, littoral drift and cyclonic storms as well as coastal development. Wave induced littoral drift and fluvial discharge causing the gradual inlet migration and has the concurrent impact on shoreline of Chilika lagoon. This study is to determine the long-term shoreline changes along the coast of Chilika lagoon. Historical satellite images were used to analyse the shoreline erosion and accretion based on statistical approach. The satellite data from 1975 to 2015 were processed by using ERDAS Imagine and the shorelines are extracted. The shoreline oscillation was analysed at an interval of 100 m along the coast of Chilika lagoon using DSAS software. Most commonly used statistical methods such as end point rate and linear regression rate are used. The shoreline change analysis for entire coast of the lagoon since 40 years (1975–2015) indicates that 62% is of accretion, 25% is under stable coast and erosion is 13%. The result reveals that the lagoon coast shows high accretion of 9.12 m/year at updrift side of the lagoon inlet whereas the downdrift side shows high erosion of ??10.73 m/year due to the wave induced northeasterly longshore sediment transport round the year and riverine discharge. This study would provide the potential erosion and accretion area at Chilika lagoon coast and would help in adaptive shoreline management plan.     

Mass Balance Estimation of Dokriani Glacier in Central Indian Himalaya Using Remote Sensing Data

Dokriani Glacier is regarded as one of the important glaciers of Bhagirathi River basin, which fed river Ganges. The length of the glacier is about 4.6 km, and snout elevation is about 4028 m m.s.l. The mass balance of this glacier was calculated using field-based measurements for few years during 1994 to 2000. However, due to remote and poor accessibility, the field-based measurements could not continue; thus, remote sensing-based methods become useful tool to estimate the long-term mass balance of the glacier. In this study, glacier mass balance has been determined using accumulation area ratio (AAR) method. Remote sensing data sets, e.g. Landsat TM, ETM?+?and OLI, have been used to estimate AAR for different years from 1994 to 2014. An attempt has also been made to develop a mathematical relationship between remote sensing-derived AAR and field-observed mass balance data of the glacier. Further, this relationship has been used to estimate mass balance of the glacier for different years using remote sensing-derived AAR. Estimated mass balance was validated from ground-observed mass balance for few years. The field-observed and remote sensing-derived mass balance data are compared and showed high correlation. It has been observed that AAR for the Dokriani Glacier varies from 0.64 to 0.71. Mass balance of the glacier was observed between ??15.54 cm and ??50.95 cm during the study period. The study highlights the application of remote sensing in mass balance study of the glaciers and impact of climate change in glaciers of Central Indian Himalaya.     

A Spectro-radiometric Analysis of Ocean Colour Sensors and Proposal for a Miniature Hyper Spectral Imager for Future

Ocean colour sensors traditionally are of fixed spectral channel systems with specified bandwidth of about 20 nm in the visible region and about 40 nm in Near Infrared region. In these systems, it is known that a radiometric error of 1% in the measurement of top of the atmosphere signal may lead to an error of 10% in the retrieved ocean upwelling radiance. In this paper we investigated the range of wavelengths participating in signal collection (effective spectral pass band, ESPB) using relative spectral response data of various sensors flown earlier. ESPB values were computed for each spectral channel for various percentages of signal and the results showed that they are quite high compared to bandwidths specified. These values were found to vary with sensor and channel. ESPB shall be small for accurate computation of spectral radiance. As the knowledge of spectral profile of the signal in the range of ESPB helps in better estimation of spectral radiance at the intended wavelengths, a miniature high performance linear variable filter based hyperspectral sensor is proposed as an alternative. We present here the design concept and report the estimated performance of such sensor that can be realized even with commercial off the shelf components for operational implementation.     

A Case Study: Heavy Rainfall Event Comparison Between Daily Satellite Rainfall Estimation Products with IMD Gridded Rainfall Over Peninsular India During 2015 Winter Monsoon

India Meteorological department (IMD) used INSAT-3D Metrological Satellite Imager data to drive two type rainfall estimation products viz-Hydro Estimate (HE) and INSAT Multi-Spectral Rainfall Algorithm (IMSRA) on half hourly rainfall rate and daily accumulated rainfall in millimeter (mm). Integrated Multi-Satellite Retrieval for GPM (IMERG) product is being derived by NASA and JAXA by using Global Precipitation Mission (GPM) satellites data. IMSRA and GPM (IMERG) are gridded data at 10 km spatial resolution and HE is available at pixel level (4 km at Nadir). IMD provides gridded rainfall data at 0.25° × 0.25° resolution which is based on wide coverage of 6955 actual observation. In present study, validation of INSAT-3D based Hydro Estimator (HE), INSAT Multi-Spectral Rainfall Algorithm (IMSRA) and Integrated Multi-Satellite Retrieval for GPM (IMERG) of Global Precipitation Mission (GPM) satellites are carried out with IMD gridded data set for heavy rainfall event during winter monsoon, over peninsular India (November–December 2015). In validation, Nash–Sutcliffe efficiencies (NSE), RMSE, Correlation, Skilled scores are calculated at grid level for heavy and very heavy rain categories and the values of NSE of HE (? 32.36, ? 3.12), GPM (? 68.67, ? 2.39) and IMSRA (? 0.02, 0.28) on 16th November 2015 and HE (? 13.65, ? 1.69), GPM (? 43.79, ? 2.94) and IMSRA (? 1.08, ? 1.60) on 2nd Dec 2015, for heavy and very heavy rainfall. On both days, HE is showing better rainfall estimate compare to GPM for Heavy rainfall and GPM showing better estimation for very heavy rainfall events. In all the cases IMSRA is underestimating, if daily rain fall exceeded 75 mm.     

Ground Based Bistatic Scatterometer Measurement for the Estimation of Growth Variables of Ladyfinger Crop at X-Band

The present study describes the ground based bistatic scatterometer measurements of ladyfinger crop at its various growth stages in the specular direction with the azimuthal angle (\( \phi = 0 \)) for the angular incidence angle ranging from 20° to 60° at the interval of 10° at HH and VV polarization. An outdoor ladyfinger crop bed of an area 4 × 4 m² was specially prepared for the ground based bistatic scatterometer measurements. The crop growth variables like vegetation water content, leaf area index, fresh biomass, and plant height were also measured at the time of each bistatic scatterometer measurement. The specular bistatic scattering coefficients were found to be decreasing with the crop growth variables up to the maturity stage and then after it increased slightly. The linear regression analysis was carried out between specular bistatic scattering coefficient and crop growth variables at all the incidence angles for HH and VV polarization to select the optimum angle of incidence and polarization for the estimation of crop growth variables. The potential of subtractive clustering based adaptive neuro-fuzzy inference system was applied for the estimation of crop growth variables. The estimated values for different crop growth variables were found almost close to the observed values.