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Abstract Due to climate change, the frequency of Glacial Lake Outburst Floods (GLOFs) is expected to increase, posing significant risks downstream. This study aims to assess the potential risks associated with GLOFs in Lower Barun Lake and their impacts on downstream settlements and the Arun-3 Hydroelectric Power Plant (HEP). Various breach scenarios were modeled using FLDWAV and HEC-RAS, incorporating avalanche events and the potential complete breach of Upper Barun Lake as triggering factors. Avalanche zones were identified and simulated using the Analytical Hierarchy Process (AHP) within a Geographic Information System (GIS) platform, and the Rapid Mass Movement Simulation (RAMMS) model was used for dynamic flow analysis. A breach hydrograph was generated with FLDWAV and routed through HEC-RAS to assess the downstream impacts. Satellite imagery and GIS were employed to map vulnerable sites and identify high-risk areas. The simulations predicted peak discharge, timing, and potential floodwater depth from Lower Barun Lake to the Arun-3 HEP. The results indicate that the Lower Barun Lake moraine dam is highly vulnerable to overtopping from avalanche-induced waves, with a 5.4 m high impulse wave potentially causing dam failure. A complete moraine dam failure results in significant downstream impacts, contrasting with minimal or negligible effects from a 25% breach. Peak discharge values ranged from 51,231 m3/s for the full dam breach scenario (100%) to 9,014 m3/s for the partial breach scenario (25%). Following a 100% breach, flooding at the Arun-3 HEP would occur after approximately 2 h, reaching a maximum discharge of 13,403.08 m3/s and a peak flood depth of 49.12 m.

Abstract Facial puffiness as a consequence of superior vena cava syndrome (SVCS) can be a presentation from which the physician would have to conjecture a diagnosis of a mediastinal mass including lymphomas. Pediatric SVCS can rapidly progress and pose a greater challenge for airway protection as was in our case.

This study was carried to understand socioeconomic factors affecting knowledge and adaption of climate change among farmers of Banke district, with the hope that knowledge about climate change and their adaption strategy can be targeted properly among farmers and their empowerment can be achieved. All the farmers from Bageshwori Village Development committee were the target population for this study. Ninety households were selected as sampling respondents for this study. The study showed that 42.22% of the respondents know about climate change. The study revealed that 35% of the respondents know about climate change through self-experiences by comparing the past and present events of climatic parameters. Local radio and social organization were the main source of their knowledge about climate change, covering share of 27% and 23% of the respondents’ means of knowledge. Age, gender and education of household head, contact to the extension workers, farming experience, presence of NGO/INGO and access to mass media found to be determinants of awareness of climate change with positive effect, except for household head age. Gender of household head, total annual income of family, farming experience, access to mass media, education of household head, farm size, presence of NGO/INGO and contact to extension workers were found to be determinants of climate change adoption. No decision is taken in vacuum, peoples’ surrounding, and experience surely affects. So, to move forward and achieve climate smart agriculture these socioeconomic factors should be accounted while planning and implementation of program, project or policies.

In this paper, we present an optimal flying path for unmanned aerial vehicle-assisted internet of things sensor networks using a location aware multi-layer information map considering different utility functions based on the sensor density, energy consumption, flight time, and flying risk level. The overall weighted sum of multi-objective utility functions is maximized using the genetic algorithm. The simulation results verify that the optimum solution points can be obtained by adjusting the weights while satisfying the required constraints.