Geoelectric characterisation of the junction of seismically active Delhi Hardwar Ridge and Delhi Sargodha Ridge.

A magnetotelluric (MT) geophysical survey for the first time has been conducted for the geoelectric characterization of the junction of the contact zone of NNE-SSW striking Delhi Hardwar Ridge (DHR) and NW-SE trending Delhi Sargodha Ridge (DSR) in the Rohtak area, Haryana which has experienced 15 earthquakes of M2.0-M4.4 from April to August 2020. A total of 08 MT sites are acquired along a NW-SE profile of length 50 km. From the 2D MT data inversion, the DHR and DSR are for the first time characterized by equal values of moderate resistivity of 100 Ohm m at two depths. The resistivity variation for DHR corresponds to 100 Ohm m from the surface to the depth of 20 km, whilst DSR is found associated with the same value of resistivity extending in the NW direction. The DHR has been found striking NE-SW with a very shallow central axis (less than 400 m) having a width of 12-15 km forming half grabens on both limbs supported by shallow faults. The DSR has been found bifurcated from DHR at a depth of 12-13 km and extended in the NW direction. The DSR has been generated due to flexure bulging caused by collision and anticlockwise rotation of the Indian plate in the Eocene period. A NE striking steep dipping reverse fault (F1) has also been identified about 15 km west of the DHR. It is inferred that the DSR got upthrusted along this fault and became shallower in the NW region. The seismicity in the Rohtak and surroundings is located at the bifurcation points of DHR and DSR and the contact zone of DSR and reverse fault F1. The reverse fault F1 is also active and has generated microseismicity in the past.

Comparative analysis of discharge and sediment flux from two contiguous glacierized basins of Central Himalaya, India.

In the present study, suspended sediment load (SSL), sediment yield and erosion rates in Pindari Glacier basin (PGB) and Kafni Glacier basin (KGB) have been estimated using daily discharge and suspended sediment concentration (SSC) data for three ablation seasons (2017-2019). For this, one meteorological observatory and two gauging sites have been established at Dwali (confluence point), and water samples have been collected twice in a day for high flow period (July to September) and daily for lean period (May, June and October). An area-velocity method and stage-discharge relationship has been established to convert water level into discharge (m3 s-1). For estimating SSC (mg/l), collected water samples have been filtered, dried, analysed and confirmed with an automatic suspended solid indicator. Further, SSL, sediment yield and erosion rates have been computed using SSC data. The results reveal that mean annual discharge in PGB (35.06 m3 s-1) has been found approximately 1.7 times higher than KGB (20.47 m3 s-1). The average SSC and SSL in PGB have been observed about 396.07 mg/l and 1928.34 tonnes, and in KGB, it is about 359.67 mg/l and 1040.26 tonnes, respectively. The SSC and SSL have followed the pattern of discharge. A significant correlation of SSC and SSL has been found with discharge in both the glacierized basins (p < 0.01). Interestingly, average annual sediment yield in PGB (3196.53 t/km2/yr) and KGB (3087.23 t/km2/yr) have been found almost identical. Likewise, the erosion rates in PGB and KGB have been witnessed about 1.18 and 1.14 mm/yr, respectively. Sediment yield and erosion rates in PGB and KGB have been found in correspondence with other basins of Central Himalaya. These findings will be beneficial for engineers and water resource managers in the management of water resources and hydropower projects in high-altitude areas and in the planning and designing of water structures (dams, reservoirs etc.) in downstream areas.

Heterogeneity in glacier thinning and slowdown of ice movement in the Garhwal Himalaya, India.

Limited ground-based surveys and extensive remote sensing analyses have confirmed glacier thinning in the Garhwal Himalaya. More detailed studies on specific glaciers and the drivers of reported changes are essential to comprehend small-scale differences in the effects of climatic warming on Himalayan glaciers. We computed elevation changes and surface flow distribution for 205 (≥0.1 km2) glaciers in the Alaknanda, Bhagirathi, and Mandakini basins, all located in the Garhwal Himalaya, India. This study also investigates a detailed integrated analysis of elevation changes and surface flow velocities for 23 glaciers with varying characteristics to understand the impact of ice thickness loss on overall glacier dynamics. We observed significant heterogeneity in glacier thinning and surface flow velocity patterns using temporal DEMs and optical satellite images with ground-based verification. The average thinning rate was found to be 0.07 ± 0.09 m a-1 from 2000 to 2015, and it increased to 0.31 ± 0.19 m a-1 from 2015 to 2020, with pronounced differences between individual glaciers. Between 2000 and 2015, Gangotri Glacier thinned nearly twice as much as the neighbouring Chorabari and Companion glaciers, which have thicker supraglacial debris that protects the beneath ice from melting. The transitional zone between debris-covered and clean ice glaciers showed substantial flow during the observation period. However, the lower reaches of their debris-covered terminus areas are almost stagnant. These glaciers experienced a significant slowdown (~25 %) between 1993-1994 and 2020-2021, and only the Gangotri Glacier was active even in its terminus region during most observational periods. The decreasing surface gradient reduces the driving stress and causes slow-down surface flow velocities and an increase in stagnant ice. Surface lowering of these glaciers may have substantial long-term impacts on downstream communities and lowland populations, including more frequent cryospheric hazards, which may threaten future water and livelihood security.

Emission of greenhouse gases due to anthropogenic activities: an environmental assessment from paddy rice fields.

Paddy rice fields (PRFs) are a potent source of global atmospheric greenhouse gases (GHGs), particularly CH4 and CO2. Despite socio-environmental importance, the emission of GHGs has rarely been measured from Haryana agricultural fields. We have used new technology to track ambient concentration and soil flux of GHGs (CH4, CO2, and H2O) near Karnal's Kuchpura agricultural fields, India. The observations were conducted using a Trace Gas Analyzer (TGA) and Soil Flux Smart Chamber over various parts, i.e., disturbed and undisturbed zone of PRFs. The undisturbed zone usually accounts for a maximum ambient concentration of ~ 2434.95 ppb and 492.46 ppm of CH4 and CO2, respectively, higher than the average global concentration. Soil flux of CH4 and CO2 was highly varied, ranging from 0.18 to 11.73 nmol m-2 s-1 and 0.13-4.98 µmol m-2 s-1, respectively. An insignificant correlation was observed between ambient concentration and soil flux of GHGs from PRFs. Waterlogged (i.e., irrigated and rain-fed) soil contributed slightly lower CH4 flux to the atmosphere. Interestingly, such an agricultural field shows low CO2 and CH4 fluxes compared to the field affected by the backfilling of rice husk ash (RHA). This article suggests farmers not mix RHA to increase soil fertility because of their adverse environmental effects. Also, this study is relevant in understanding the GHGs' emissions from paddy rice fields to the atmosphere, their impacts, and mitigating measures for a healthy ecosystem.

Explicating the amino acid effects for methane storage in hydrate form.

Methane emissions increase day by day into the atmosphere and influence global temperatures. The necessity to capture these emissions at the source point is a primary concern. Several methods/techniques are being adopted to capture these emissions. The methane hydrates could be a viable method among them. The present study exposes various amino acids' effects in methane hydrate formation. The formation temperatures are around ∼268 to 273 K except for l-cys, which is about ∼277 K. The required subcooling for hydrates to trigger is high and is increasing in the order l-thr > l-met > l-phe > l-val > l-cys. The methane hydrate conversion is high in the presence of nearly all the amino acids with methane uptake capacity of ∼80-85%, except l-thr, for which it is only 30% of the total uptake capacity. The side chain of l-thr comprises the hydroxyl group, making it a polar and uncharged amino acid. It is ascertained that hydroxyl groups alone can form hydrogen bonds with water, increasing the hydrophilicity and solubility of molecules, causing lesser conversion in the l-thr system. The gas uptake kinetics is faster in l-met and l-phe systems (t 90 ∼ 40 min), and sluggish kinetics is observed in l-cys, l-val, and l-thr systems. The investigations positively indicate using amino acids, l-met, l-phe, l-cys, and l-val as efficient materials for methane gas capture and storage in hydrate form, although not l-thr. Amino acids are readily dissolvable in water and could be easily pelletized for methane gas storage and transportation.

Potential seismic precursors and surficial dynamics of a deadly Himalayan disaster: an early warning approach.

On 7 February 2021, Chamoli district (Uttarakhand, India) was devastated by a deadly rock-ice avalanche that led to a large causality of more than 200 people and a huge economic loss. We found noteworthy sequence of precursory signals of main failure/detachment preceded by a dynamic nucleation phase. The rock-ice avalanche appears to have been initiated by seismic precursors which were continuously active for 2:30 h prior to main detachment. The seismic amplitude, frequency characteristics and signal-to-noise ratio variation of detected tremors indicate static to dynamic changes in nucleation phase located at the source of detached wedge. The characteristics of seismic data distinguished debris flow and hitting obstacles from other seismic sources and allowed the estimations of debris flow speed. We analyzed and verified the seismic signals with field evidences to estimate the associated impacts and velocity of dynamic flow. The proximal high-quality seismic data allowed us to reconstruct the complete chronological sequence and evaluate impacts since the initiation of nucleation phase to its advancement. Furthermore, we suggest that real-time seismic monitoring with existing network and future deployment of integrated dense network can be used for forecasting of flow events and hazard mitigation in the downstream.

Submarine canyon systems focusing sub-surface fluid in the Canterbury Basin, South Island, New Zealand.

This work uses a high-quality 3D seismic volume from offshore Canterbury Basin, New Zealand, to investigate how submarine canyon systems can focus sub-surface fluid. The seismic volume was structurally conditioned to improve the contrast in seismic reflections, preserving their lateral continuity. It reveals multiple pockmarks, eroded gullies and intra-slope lobe complexes occurring in association with the Waitaki Submarine Canyon. Pockmarks are densely clustered on the northern bank of the canyon and occur at a water depth of 500-900 m. In parallel, near-seafloor strata contain channel-fill deposits, channel lobes, meandering channel belts and overbank sediments deposited downslope of the submarine canyon. We propose that subsurface fluid migrates from relatively deep Cretaceous strata through shallow channel-fill deposits and lobes to latter seep out through the canyon and associated gullies. The new, reprocessed Fluid Cube meta-attribute confirms that fluids have seeped out through the eroded walls of the Waitaki Canyon, with such a seepage generating seafloor depressions in its northern bank. Our findings stress the importance of shallow reservoirs (channel-fill deposits and lobes) as potential repositories for fluid, hydrocarbons, or geothermal energy on continental margins across the world.

A machine learning tool for interpretation of Mass Transport Deposits from seismic data.

Machine learning is a tool that allows machines or intelligent systems to learn and get equipped to solve complex problems in predicting reliable outcome. The learning process consists of a set of computer algorithms that are employed to a small segment of data with a view to speed up realistic interpretation from entire data without extensive human intervention. Here we present an approach of supervised learning based on artificial neural network to automate the process of delineating structural distribution of Mass Transport Deposit (MTD) from 3D reflection seismic data. The responses, defined by a set of individual attributes, corresponding to the MTD, are computed from seismic volume and amalgamated them into a hybrid attribute. This generated new attribute, called as MTD Cube meta-attribute, does not only define the subsurface architecture of MTD distinctly but also reduces the human involvement thereby accelerating the process of interpretation. The system, after being fully trained, quality checked and validated, automatically delimits the structural geometry of MTDs within the Karewa prospect in northern Taranaki Basin off New Zealand, where MTDs are evidenced.

Acoustic reflections in the water column of Krishna-Godavari offshore basin, Bay of Bengal.

Seismic oceanographic studies from various oceans worldwide have indicated that the acoustic reflections are mostly observed along thermal boundaries within the water column. However, the authors present a case study of seismic data from Krishna-Godavari Basin which shows that salinity variations also play an important role in the occurrence of water column reflections. The observed reflection is modeled using the reflectivity series derived from the salinity and temperature profiles from a nearby Conductivity-Temperature-Depth (CTD) location. Sensitivity analysis of temperature and salinity on soundspeed shows that the effect of salinity cannot be ignored for modeling acoustic reflections. The synthetic seismogram matches well with the observed reflection seismic data. Remarkable similarities between the reflection seismic and the salinity profile in the upper thermocline suggest the importance of salinity variations on the water column reflection. Furthermore, impedance inversion of the reflectivity data reveals several thermohaline structures in the water column. The origin of these thermohaline structures is largely unaddressed and may be attributed to the fresh water influx coming from Himalayan and Peninsular rivers or due to the presence of different water masses in the Indian Ocean which warrants a detailed study using concurrent seismic and CTD data.