13 research outputs found

    Assessment of channel shifting of Karnali Megafan in Nepal using remote sensing and GIS

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    River flow exhibits morphological changes over time. The shifting of river channels is a common natural phenomenon which often poses risk to life and property. Channel shifting is mostly associated..

    Farmers’ Perception of Climate Change and Its Impacts on Agriculture

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    Climate change and climate variability drive rapid glacier melt and snowpack loss, extreme precipitation and temperature events, and alteration of water availability in the Himalayas. There is increasing observational evidence of climate change impacts on water resource availability and agricultural productivity in the central Himalayan region. Here, we assess the farmers’ perception of climate change and its impacts on agriculture in western Nepal. We interviewed 554 households and conducted eight focus group discussions to collect farmers’ perceptions of temperature and rainfall characteristics, water availability, onset and duration of different seasons, and the impacts of such changes on their lives and livelihoods. Our results indicate that the farmers’ perceptions of rising annual and summer temperatures are consistent with observations. Perception, however, contradicts observed trends in winter temperature, as well as annual, monsoon, and winter precipitation. In addition, farmers are increasingly facing incidences of extreme events, including rainfall, floods, landslides, and droughts. These hazards often impact agricultural production, reducing household income and exacerbating the economic impacts on subsistence farmers. Integrated assessment of farmers’ perceptions and hydrometeorological observations is crucial to improving climate change impact assessment and informing the design of mitigation and adaptation strategies

    Natural Hazards Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

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    This article is about the state of ICON principles Goldman et al. (2021), https://doi. org/10.1029/2021EO153180 in natural hazards and a discussion on the opportunities and challenges of adopting them. Natural hazards pose risks to society, infrastructure, and the environment. Hazard interactions and their cascading phenomena in space and time can further intensify the impacts. Natural hazards’ risks are expected to increase in the future due to environmental, demographic, and socioeconomic changes. It is important to quantify and effectively communicate risks to inform the design and implementation of risk mitigation and adaptation strategies. Multihazard multisector risk management poses several nontrivial challenges, including: (a) integrated risk assessment, (b) Earth system data-model fusion, (c) uncertainty quantification and communication, and (d) crossing traditional disciplinary boundaries. Here, we review these challenges, highlight current research and operational endeavors, and underscore diverse research opportunities. We emphasize the need for integrated approaches, coordinated processes, open science, and networked efforts (ICON) for multihazard multisector risk management

    Nepal Himalaya Offers Considerable Potential for Pumped Storage Hydropower

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    There is a pressing need for a transition from fossil-fuel to renewable energy to meet the increasing energy demands and reduce greenhouse gas emissions. The Nepal Himalaya possesses substantial renewable energy potential that can be harnessed through hydropower projects due to its peculiar topographic characteristics and abundant water resources. However, the current exploitation rate is low owing to the predominance of run-of-river hydropower systems to support the nation's power system. The utility-scale storage facility is crucial in the load scenario of an integrated Nepalese power system to manage diurnal variation, peak demand, and penetration of intermittent energy sources. In this study, we first identify the potential of pumped storage hydropower across the country under multiple configurations by pairing lakes, hydropower projects, rivers, and available flat terrains. We then identify technically feasible pairs from those of potential locations. Infrastructural, environmental, operational, and other technical constraints govern the choice of feasible locations. We find the flat land-to-river configuration most promising over other configurations for Nepal. Our results provide insight into the potential of pumped storage hydropower and are of practical importance in planning sustainable power systems in the Himalayas

    Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

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    BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

    Developing Sediment Transport and Deposition Prediction Model of Lower Ohio River near the Olmsted Locks and Dam Area

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    The present study focuses on the sediment deposition and consequent dredging issues in Lower Ohio River at the Olmsted Locks and Dam area-River mile (RM)-964.4 during the ongoing in-the-wet construction methodology. The study reach is between Locks and Dam 53 (RM 962.6) at upstream, and RM 970 at downstream. One dimensional (1-D) HEC-RAS numerical modeling in conjunction with Arc-GIS was employed. Stream flow measurements, velocity, incoming sediment concentration, bed gradation, and annual hydrographic survey data acquired from public archives of USGS and USACE Louisville District were used as inputs. The model was subjected to the 1-D quasi-unsteady and completely unsteady sediment transport module, available in the latest HEC-RAS 5.0 Beta release. Calibration and validation of the hydrodynamic and sediment models were performed using measured water surface elevation, velocity, and sediment loads at measured sections. Post-model calibration and validation, deposition to excavated cross-sections for future dam shells at Olmsted was predicted, which warrants dredging. The study attempted to analyze the sediment transport trend with the focus on depositionat Olmsted Locks and Dam area using the sensitivity analysis approach of transport capacity functions. Moreover, the capability of 1-D HEC-RAS quasi-unsteady and completely unsteady models were assessed in prediction of sediment deposition in the construction area (dam shells excavation area). A temporal deposition prediction model was developed that can potentially replace the current ad-hoc approach used to determine the dredging schedule. Likewise, a representative environmental risk associated with sedimentation in the study area was examined. The model can potentially be used as a decision support tool to analyze the long term impact of sedimentation in the vicinity of Olmsted Locks and Dam if further updates on the river bathymetry, and specific field data are supplemented to the model

    Machine Learning for Postprocessing Medium-range Ensemble Streamflow Forecasts

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    Skillful streamflow forecasts can inform decisions in various areas of water policy and management. We integrate numerical weather prediction ensembles and a distributed hydrological model to generate ensemble streamflow forecasts at medium-range lead times (1 - 7 days). We demonstrate a case study for machine learning application in postprocessing ensemble streamflow forecasts in the Upper Susquehanna River basin in the eastern United States. For forecast verification, we use different metrics such as skill score and reliability diagram conditioned upon the lead time, flow threshold, and season. The verification results show that the machine learning postprocessor can improve streamflow forecasts relative to low complexity forecasts (e.g., climatological and temporal persistence) as well as deterministic and raw ensemble forecasts. As compared to the raw ensembles, relative gain in forecast skill from postprocessor is generally higher at medium-range timescales compared to shorter lead times; high flows compared to low-moderate flows, and warm-season compared to the cool ones. Overall, our results highlight the benefits of machine learning in many aspects for improving both the skill and reliability of streamflow forecasts

    Assessment of Population Status and Diurnal Behaviour of White-rumped Vulture (Gyps bengalensis) in Ghachowk, Kaski, Nepal

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    Vulture Safe Feeding Sites (VSFS) provide diclofenac-free food and create an ideal environment for long-term ecological research on vultures. This study determines the population status and investigates the diurnal behavior White-rumped Vulture (Gyps bengalensis) at the Ghachowk VSFS in Kaski, Nepal. We deployed the absolute count method to determine population of White-rumped Vulture (Gyps bengalensis), while scan sampling was applied to investigate their diurnal behaviour. The observed population of Gyps bengalensis ranged from 34 to 65 individuals (with an average of 50±10, based on a sample size of 9). Throughout the daytime, a total of 1651 instances of 11 distinct activities were recorded for the species in 729 separate observations. The most frequent daytime behaviour observed was perching (28%) followed by preening (14%), basking (13%), scratching (13%) flapping (10%), flying (9%) and disturbance (7%). Other behaviors, like feeding, sleeping (roosting), fighting (competition), and bathing, were observed less frequently (<2% each). Perching occurred most frequently during heavy rain, accounting for 66% of the observations, and in the late afternoon, representing 36% of the instances. Basking was most commonly observed during partly sunny conditions, comprising 26% of the observations, and in the noon hours, representing 20% of the instances. Scratching behavior was most frequently observed during clear weather, accounting for 16% of the observations, and during cloudy conditions and in the morning, accounting for 14% of the instances. In the Ghachowk VSFS, other associated species with White-rumped Vulture were Red-headed Vulture Sarcogyps calvus, Egyptian Vulture Neophron percnopterus, and Slender-billed Vulture Gyps tenuirostris. This study plays a pivotal role in uncovering the conservation requirements especially in reducing social taboos of the tradition communities regarding this critically endangered species which needs strong social support for its long-term conservation
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