Research papers in International Journals

Glacial lake expansion and GLOF hazard assessment of Kedartal, upper Ganga basin: insights from remote sensing, climatological and 2D hydro-dynamic modelling

2026-09-11T05:16:06Z

Glacial lake expansion and GLOF hazard assessment of Kedartal, upper Ganga basin: insights from remote sensing, climatological and 2D hydro-dynamic modelling Patel, Lavkush Kumar; Yadav, Shiv Shankar; Padhi, Aadarsh; Thapliyal, Madhusudan; Singh, Surjeet The Hindu Kush Himalaya (HKH) is among the world’s most vulnerable mountain regions, where accelerated glacier retreat has driven the expansion of glacial lakes and increased the potential for Glacial Lake Outburst Floods (GLOFs). This study assesses the potential GLOF hazard associated with Kedartal Lake, a lateral moraine- dammed glacial lake in the Upper Ganga Basin, by integrating climatic trend analysis with process-based hydrodynamic model ling. Multi-temporal satellite observations (2001–2025) with historical mapping, were used to quantify lake evolution. While two- dimensional hydrodynamic model (HEC-RAS) simulated down stream flood propagation under a worst-case dam breach scenario. Results revealed a seasonal expansion of lake area from 64455:86m (1990) to 105772:99m2 (2020), and 1; 33; 823:1m (2025), representing ~64.1% seasonal variation since 1990. The GLOF simulation results showed a high magnitude flood wave with the peak dis charge ~2;800m3 3=s within 15 minutes after initiation at the outlet. The flood wave attenuates as it travels down the Kedar-Ganga valley, reaching Gangotri town with a peak discharge of ~1;450m =s almost 45 minutes after the breach. Flood routing models indicate flow depths up to 2 metres in narrow gorge sec tions, and inundation depths ranging from 0 to 15 metres in the built-up areas near the confluence. Regional climatic analysis reveals a statistically significant warming trend (~0.013 °C yr; p < 0.001) and increasing extreme precipitation events, reinforcing climatic forcing as a primary driver of glacier mass loss and lake expansion. The projected hazard, consistent with SSP-based climate forecast, indicates a risk to Gangotri town. These findings demonstrate the utility of the proposed framework for identifying essential datasets, analytical methods, and monitoring requirements to support preliminary GLOF hazard assessment and future risk management in the basin.

Ice-flux divergence and strain rates reveal compressive-flow hotspots on Gangotri glacier

2026-05-19T05:23:21Z

Ice-flux divergence and strain rates reveal compressive-flow hotspots on Gangotri glacier Islam, Anikul; Swarnkar, Somil; Varade, Divyesh; Sinha, Rajiv Observation of glacier dynamics are critical for assessing hydro-climate processes in the high altitude regions of the world. This study investigated critical glacier ice parameters such as the ice flux divergence (IFD), surface mass balance (SMB) and the spatial pattern of ice surface deformation through logarithmic strain rate of the Gangotri glacier in the upper Bhagirathi basin using fully distributed models based purely on remote sensing data. The primary input for the investigations are based on the ice-thickness change rate, glacier velocity and the digital elevation model (DEM). The SMB referred to as the sum of the vertical and lateral changes of the glacier was observed to be 0.97 m of ice equivalent(m i.e.) yr 1 , indicating significance mass loss over the study period. The results derive several alignments with other published studies, and reveal key insights on the internal glacier processes through critical parameters such as highly variable longitudinal and shear strain rate indicated by standard deviations exceeding 0.025 yr 1 and 0.013 yr 1 , respectively. These highly variable and negative strain rates indicate significant compressive deformation of the glacier in certain regions of the ablation zone, resulting in ice cliffs and large crevasses that were observed in other studies.

Assessing Glacier Dynamics and Debris-Cover-Controlled Ablation in Svalbard: Insights from Gåsbreen (2003 2023)

2026-05-19T05:05:32Z

Assessing Glacier Dynamics and Debris-Cover-Controlled Ablation in Svalbard: Insights from Gåsbreen (2003 2023) Patel, Lavkush Kumar; Głowacki, Oskar; Jain, Vineet; Moskalik, Mateusz The Svalbard Archipelago is a highly glaciated region, making it particularly sensitive to progressive climate shifts. This sensitivity is evident in the major changes observed in glacier dynamics. For this reason, both experimental observations and long-term monitoring of glaciers' mass loss in Svalbard are necessary and urgent. Responding to these needs, this study presents a quantitative analysis of melt rate and mass balance of Gåsbreen – a debris-covered land-based glacier located in Hornsund fjord, Spitsbergen. We combined a direct observation on the glacier with satellite data spanning the period 2003–2023 to quantify glacier dynamics and the role of debris cover on glacier ablation. Results covering the study period (2003–2023) indicate a shrinking glacier area (1.47 ±0.07 km 2 ) and a notable retreat of the lower terminus (280 ± 45 m at a rate of 13.3 ma melting doubled in recent years (2016–2023: 0.78 ± 0.07 km 2 a 1 1 ). Notably the rate of ). The surface elevation changes across the glacier ranged within ±2 m a 1 , indicating moderate spatial variability between the ablation and accumulation zones. The computed total ice flux was ~9.9 × 10 5 m yr 1 m 3 yr 1 , corresponding to a mean emergence velocity of 0.09 . Overall, Gåsbreen exhibited a slight positive average mass balance of 0.13 m w.e. a 1 , suggesting that accumulation marginally exceeded ablation during the study period. Approximately 10% of the glacier area was covered by debris during the study period, with a noticeable increase in debris accumulation observed during 2016–2023. Importantly, analysis of ablation rates revealed varying thinning rates across different debris thickness categories, with a significant reduction (25–30%) in ablation rates observed over thicker debris. The study also highlights the projected increase in debris cover and its implications for glacier morphology including the formation of supraglacial ponds and ice cliffs, which are anticipated to contribute significantly to total mass loss. This quantitative assessment provides new insights into the complex interplay between debris thickness and glacier response to the warming climate.

Large-scale modeling of solar water pumps using machine learning

2026-01-07T05:42:32Z

Large-scale modeling of solar water pumps using machine learning Zuffinetti, Guillaume; Meunier, Simon; Hudelot, Celine; John MacAllister, Donald; Krishan, Gopali; Lutton, Evelyne; Bhattacharya, Prosun; Kitanidis, Peter K.; MacDonald, Alan M. Photovoltaic Groundwater Pumping Systems (PVGWPSs) have experienced growing interest, particularly in two key regions. In Africa, they offer a means to improve water availability for millions. In northern India, they could help decarbonize the agricultural sector. However, large-scale deployment must be approached carefully to avoid risks such as groundwater overextraction or widespread unmet irrigation demand. To support informed deployment, a large-scale, physics-based, dynamic PVGWPS model is introduced, that simulates pumping ca pacities of PVGWPS. Given the computational intensity of this model, machine learning-based emulators are explored to replicate its results more efficiently without significant loss in accuracy. The emulator operates in two stages. First, it predicts whether the motor-pump will stop due to water level dropping below the operational threshold. Among the models tested, the Gradient Boosting Classifier model performed best. Second, when no stoppage is predicted, the emulator estimates the pumping capacity of the PVGWPS. Among the models tested for this second task, the Random Forest Regressor gave the most accurate results. Applied to datasets from Africa and the Indo-Gangetic Basin within India, the emulator achieved high accuracy (R 2 ≥ 0.99, NRMSE ≤ 5 %) while reducing computation time by more than a factor of 1500. The emulators thus offer high computational speed and sufficient accuracy to open the way to addressing large-scale dispatch problems, such as the optimal positioning and pre-sizing of PVGWPSs at regional, national, or even continental scales while considering a large number of possible climate scenarios. Coupled with sustainability analyses (not explored in this study), they could serve as powerful upstream decision-support tools for PVGWPSs planning, complementing more detailed, site-specific analyses .