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Basin-scale spatio-temporal development of glacial lakes in the Hindukush-Karakoram-Himalayas
No full textGlacial lakes are expanding exponentially in the cryospheric environment of the Hindukush-Karakoram-Himalayas (HKH). Rapid glacier melting due to an above mean global annual temperature increase in HKH is attributed as the main reason for the expansion of the glacial lakes. The rapid expansion of glacial lakes increases the risk of future Glacial Lake Outburst Floods (GLOFs) events in the HKH. In the present study, glacial lake inventories for the Indus, Ganga and Brahmaputra (IGB) river basins in the HKH were generated for 1990, 2000, 2010 and 2020 using Landsat (TM & OLI) at the sub-basin level to understand the spatio-temporal and regional patterns of glacial lakes dynamics, elevational evolution, and changes in the typology. We mapped 17,641 glacial lakes (area: 1082.57 ± 192.601 km2) in 1990, 18,206 (area: 1120.95 ± 198.49 km2) in 2000, 18,399 (area: 1147.12 ± 201.26 km2) in 2010, and 19,284 (area: 1191.81 ± 209.21 km2) in 2020. Between 1990 and 2020, IGB basins showed an increase of 9.31 % in total number and 10.09 % in total area of glacial lakes. In 2020, the Brahmaputra basin had the maximum total area (area: 763.59 132.14 km2), followed by Indus basin ± (area: 217.47 ± 43.39 km2) and the Ganga basin (area: 210.74 ± 33.66 km2). However, between 1990 and 2020, glacial lakes in the Ganga basin (n: 22.08 %) had the highest growth rate, followed by the Indus basin (n: 14.73 %) and the Brahmaputra basin (n: 4.41 %). In 2020, 76.11 % of glacial lakes were end-moraine-dammed M(e) lakes, followed by other bedrock-dammed B(o) lakes (16.45 %), supraglacial lakes (2.79 %), lateral moraine-dammed M(l) lakes (2 %), cirque B(c) lakes (1.06 %), other moraine-dammed M(o) lakes (0.38 %), and other glacial (O) lakes (1.18 %). Given the rapid growth of glacial lakes in the region along with their likely flood volumes and damage potential in case of their failures, the present study will be of importance for disaster management authorities, an important input for detection of potentially hazardous glacial lakes and for development of mitigation strategies to minimize the impact of potential future GLOF events
Development of multimodel-based hydrologic outlook for India
No full textReal-time monitoring and early warning systems for hydrological variables are essential for the decision making for managing water resources and agricultural activities. Notwithstanding the considerable progress in operational weather and climate forecast in India, efforts to develop a multimodel-based hydrological outlook utilizing the meteorological forecast have been lacking. Here using gridded observations, meteorological forecast, and ensemble of three hydrological models (VIC, Noah-MP, and H08), we examine the potential of meteorological forecast for the development of a hydrologic outlook at a short-to-subseasonal lead time. We evaluate the role of multivariate bias correction that ensures co-variability of precipitation and temperature in the monsoonal climate on the prediction skills of hydrologic outlook components (precipitation, temperature, evapotranspiration, runoff, soil moisture, and streamflow). The raw forecast from the Extended Range Forecast System (ERFS) showed overall wet bias in precipitation and warm bias in maximum and minimum temperatures, which was significantly improved after the multivariate bias correction. As the bias correction of meteorological forecast and post-processing of streamflow resulted in the best prediction skills, we used it to develop the hydrologic outlook. The developed hydrologic outlook demonstrated reasonable forecast skills at 1-30 day lead time for extreme dry and wet conditions. The multimodel-based hydrologic outlook can assist the decision making in water resources and agriculture in India
Recent drying of the Ganga River is unprecedented in the last 1,300 years
No full textThe Ganga River basin, critical to over 600 million people, is experiencing a severe and unprecedented drying trend, threatening water and food security. Using streamflow reconstructions spanning 1,300 y (700–2012 C.E.) from instrumental data, paleohydrological records, and hydrological modeling, we show that drying from 1991 to 2020 is unmatched in the past millennium. Streamflow decline since the 1990s, driven by frequent and prolonged droughts, is 76% more intense than the 16th-century drought—the closest historical analogue. This drying exceeds natural variability, highlighting the dominant role of anthropogenic factors. Despite CMIP6 models projecting increased streamflow under warming scenarios, the recent decline indicates complexities associated with future water availability projections. Our findings underscore the urgent need to examine the interactions among the factors that control summer monsoon precipitation, including large−scale climate variability and anthropogenic forcings. Better constraints on these processes in climate models will be essential for improving future monsoon projections and implementing adaptive water management strategies to secure the Ganga basin’s freshwater availability under a changing climate
Increased Drought Synchronicity in Indian Rivers Under Anthropogenic Warming
No full textSynchronous streamflow droughts across multiple river basins can lead to large-scale water scarcity and disruptions in food and water security. However, the drivers and changes in drought synchronicity across Indian rivers remain unexplored due to the limited length of instrumental records. Using streamflow observations and paleohydrological records, we reconstructed streamflow for 45 gauge stations on major Indian rivers, spanning 1200–2012 C.E., to examine the changes and drivers of streamflow drought synchronicity. Our reconstructed streamflow record for the past ∼800 years shows that streamflow drought frequency and synchronicity have increased during the recent period (1850–2012). While past major synchronous droughts in Indian rivers were associated with El Niño and positive Indian Ocean Dipole (IOD) conditions, the recent increase in streamflow drought synchronicity is linked with anthropogenic climate warming. Simulations of the Paleo Model Intercomparison Project Phase 4 (PMIP4-CMIP6) that include both natural and anthropogenic forcings confirm the role of anthropogenic warming in enhancing drought synchronicity. Our findings provide critical insights into the long-term variability of droughts in Indian rivers and underscore the growing risk of large-scale water scarcity
Dynamics of EPBs and MSTIDs interaction during the post-midnight sector over the Indian low-latitude region
No full textWe present evidence of the merging of Equatorial Plasma Bubbles (EPBs) with Medium-Scale Travelling Ionospheric Disturbances (MSTIDs) during the post-midnight sector over the Indian region, observed on the night of 28th January 2011, a typical spread F event. The wavefront of the MSTIDs was aligned from northwest to southeast, propagating southwestward. In this study, we analyze airglow data from OI 630.0 nm emission recorded by an all-sky imager (ASI) located at Kolhapur (16.8°N, 74.2°E). The onset of EPBs was observed around 13:30 UT. Notably, eastward-moving EPBs began to merge with the dark wavefronts of MSTIDs around 19:50 UT, with the process completing by 21:45 UT. During this merging process, the drift velocity of EPBs decreased from 100 m/s to 50 m/s which later merged with the dark fronts of MSTIDs, as noted in OI 630.0 nm images. This interaction resulted in structural changes to the eastward drifting EPBs. The electrodynamics associated with this novel event is elaborated in this paper
Beyond Born-Oppenheimer Treatment for Multi-State Photoelectron Spectra, Phase Transitions of Solids and Scattering Processes
No full textThe "completeness" and "accuracy" of first principle based Beyond Born-Oppenheimer (BBO) theory is reviewed with its theoretical developments and wide applications on various realistic spectroscopic systems, scattering processes and pervoskite molecules exhibiting phase transition phenomena. Over the last two decades, our group has formulated as well as implemented the BBO treatment to construct diabatic Hamiltonian for several spectroscopically interesting molecules (NO 2 radical, Na3 and K3 clusters, NO3, C6H6+,1,3,5−C6H3F3+ and C4N2H4), octahedral units of perovskites (MnO69- and TiO68-) involving solid state phenomenon as well as triatomic reactive scattering processes (H3+, HeH2+ and F+H2) to depict the effects of electron-nuclear couplings. Such diabatic Hamiltonians have been further used to perform quantum dynamical calculations to obtain observables (photoelectron spectra for spectroscopic/solid state systems and cross-sections/rate constants for scattering processes), which show excellent agreement with the recent experimental findings. In summary, this article provides the current perspective of BBO approach as well as Jahn-Teller (JT) theory with various applications on molecular systems/chemical processes
Functionalized metal organic framework (MIL-101(Cr)) as selective adsorbent for the mitigation of uranium (VI) from contaminated lake water.
No full textMetal-organic frameworks (MOFs) received much attention due to their distinct porous structure. Diaminomaleonitrile (DAMN) functionalized chromium (III) terephthalate MOF (MIL-101(Cr)) was developed using a facile method as a promising adsorbent for U removal. The functionalized adsorbent contained abundant amine and cyanide groups onto the coordinatively unsaturated metal binding sites. The DAMN-functionalized MIL-101(Cr) was thoroughly characterized. The adsorbent exhibited maximum Langmuir adsorption capacity of 743 mg/g for U at pH 6 and room temperature. Different coexisting ions, having concentration within 10–50 mg/L, show negligible influence on the U adsorption (86.0–99.3 % removal). The effects of other ions on the U removal were studied in terms of U ionic speciation in the aqueous solution. The surface-grafted −C≡N and –NH2 groups were responsible for the coordinative interactions with the U(VI) ionic moieties. The MIL-101(Cr)_DAMN adsorbent was also subjected to five consecutive adsorption–desorption cycles, with >90.5 % U removal after the 5th cycle. An adsorption-pore diffusion based transport model was used to analyze the adsorption kinetics and estimation of the pore diffusivity. The effectiveness of the developed adsorbent was also demonstrated by a batch kinetic run using U contaminated lake water. In general, this research demonstrates the straightforward design and development of DAMN-functionalized MIL-101(Cr) as an effective adsorbent for the selective uptake of U(VI) from aqueous medium
Polythiophene incorporated polysulfone blend membranes for effective removal of zinc and iron from electroplating effluent: Experimental studies and performance modelling
No full textPolythiophene (pTh) was doped in a polysulfone (Psf) matrix to form ultrafiltration (UF) grade blend membranes. The membranes showed negative surface potential at neutral pH condition (zeta potential: −18 mV for membrane M-0.5 at pH 7) along with good adsorption capacities for various heavy metals. The optimum membrane M-0.5 (with 0.5 wt% pTh concentration) had the highest heavy metal selectivity (adsorption capacities of 81, 64.4, 59 and 51 mg/g for lead, iron, zinc and copper ions, respectively) with a permeability of 4.92 × 10-11 m/Pa.s. Furthermore, the potential of the blend M-0.5 membrane was investigated for the reduction of Zn(II) and Fe(II) from an electroplating effluent using a two-stage UF to reduce metal ion concentration below the dischargeable limit. The membrane M-0.5 had a breakthrough time of 16 h for the synthetic solution and 10 h for the 2nd stage of industrial wastewater. A two-dimensional multicomponent transient convective-adsorption model was utilized to predict the membrane performance
Observation of gravitational waves from the coalescence of a 2.5–4.5 M<sub>⊙</sub> compact object and a neutron star
No full textWe report the observation of a coalescing compact binary with component masses 2.5–4.5 M⊙ and 1.2–2.0 M⊙ (all measurements quoted at the 90% credible level). The gravitational-wave signal GW230529_181500 was observed during the fourth observing run of the LIGO–Virgo–KAGRA detector network on 2023 May 29 by the LIGO Livingston observatory. The primary component of the source has a mass less than 5 M⊙ at 99% credibility. We cannot definitively determine from gravitational-wave data alone whether either component of the source is a neutron star or a black hole. However, given existing estimates of the maximum neutron star mass, we find the most probable interpretation of the source to be the coalescence of a neutron star with a black hole that has a mass between the most massive neutron stars and the least massive black holes observed in the Galaxy. We provisionally estimate a merger rate density of 55-47+127 Gpc-3yr-1
for compact binary coalescences with properties similar to the source of GW230529_181500; assuming that the source is a neutron star–black hole merger, GW230529_181500-like sources may make up the majority of neutron star–black hole coalescences. The discovery of this system implies an increase in the expected rate of neutron star–black hole mergers with electromagnetic counterparts and provides further evidence for compact objects existing within the purported lower mass gap
Roles of network topology in the relaxation dynamics of simple chemical reaction network models
No full textUnderstanding the relationship between the structure of chemical reaction networks and their reaction dynamics is essential for unveiling the design principles of living organisms. However, while some network-structural features are known to relate to the steady-state characteristics of chemical reaction networks, mathematical frameworks describing the links between out-of-steady-state dynamics and network structure are still underdeveloped. Here, we characterize the out-of-steady-state behavior of a class of artificial chemical reaction networks consisting of the ligation and splitting reactions of polymers. Within this class, we examine minimal networks that can convert a given set of sources (e.g., nutrients) to a specified set of targets (e.g., biomass precursors). By exploring the dynamics of the models with a simple setup, we find three distinct types of relaxation dynamics after perturbation from a steady-state: exponential-, power-law-, and plateau-dominated. We computationally show that we can predict this out-of-steady-state dynamical behavior from just three features computed from the network's stoichiometric matrix, namely, (1) the rank gap, determining the existence of a steady-state; (2) the left null-space, being related to conserved quantities in the dynamics; and (3) the stoichiometric cone, dictating the range of achievable chemical concentrations. We further demonstrate that these three quantities relates to the type of relaxation dynamics of combinations of our minimal networks, larger networks with many redundant pathways, and a real example of a metabolic network. The relationship between the topological features of reaction networks and the relaxation dynamics presented here are useful clues for understanding the design of metabolic reaction networks as well as industrially useful chemical production pathways