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Your search keyword '"Nikolopoulos, Efthymios I."' showing total 207 results
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207 results on '"Nikolopoulos, Efthymios I."'

4. Satellite-derived foresummer drought sensitivity of plant productivity in Rocky Mountain headwater catchments: spatial heterogeneity and geological-geomorphological control

Author

Wainwright, Haruko M, Steefel, Christoph, Trutner, Sarah D, Henderson, Amanda N, Nikolopoulos, Efthymios I, Wilmer, Chelsea F, Chadwick, K Dana, Falco, Nicola, Schaettle, Karl Bernard, Brown, James Bentley, Steltzer, Heidi, Williams, Kenneth H, Hubbard, Susan S, and Enquist, Brian J

Subjects
Earth Sciences, Atmospheric Sciences, Physical Geography and Environmental Geoscience, Biological Sciences, random forest, Rocky Mountains, NDVI, foresummer drought sensitivity, Meteorology & Atmospheric Sciences
Abstract

Long-term plot-scale studies have found water limitation to be a key factor driving ecosystem productivity in the Rocky Mountains. Specifically, the intensity of early summer (the 'foresummer' period from May to June) drought conditions appears to impose critical controls on peak ecosystem productivity. This study aims to (1) assess the importance of early snowmelt and foresummer drought in controlling peak plant productivity, based on the historical Landsat normalized-difference vegetation index (NDVI) and climate data; (2) map the spatial heterogeneity of foresummer drought sensitivity; and (3) identify the environmental controls (e.g. geomorphology, elevation, geology, plant types) on drought sensitivity. Our domain (15 15 km) includes four drainages within the East Water watershed near Gothic, Colorado, USA. We define foresummer drought sensitivity based on the regression slopes of the annual peak NDVI against the June Palmer Drought Severity Index between 1992 and 2010. Results show that foresummer drought sensitivity is spatially heterogeneous, and primarily dependent on the plant type and elevation. In support of the plot-based studies, we find that years with earlier snowmelt and drier foresummer conditions lead to lower peak NDVI; particularly in the low-elevation regions. Using random forest analysis, we identify additional key controls related to surface energy exchanges (i.e. potential net radiation), hydrological processes (i.e. microtopography and slope), and underlying geology. This remote-sensing-based approach for quantifying foresummer drought sensitivity can be used to identify the regions that are vulnerable or resilient to climate perturbations, as well as to inform future sampling, characterization, and modeling studies.

Published
2020

10. How deregulation, drought and increasing fire impact Amazonian biodiversity

Author

Feng, Xiao, Merow, Cory, Liu, Zhihua, Park, Daniel S., Roehrdanz, Patrick R., Maitner, Brian, Newman, Erica A., Boyle, Brad L., Lien, Aaron, Burger, Joseph R., Pires, Mathias M., Brando, Paulo M., Bush, Mark B., McMichael, Crystal N. H., Neves, Danilo M., Nikolopoulos, Efthymios I., Saleska, Scott R., Hannah, Lee, Breshears, David D., Evans, Tom P., Soto, José R., Ernst, Kacey C., and Enquist, Brian J.

Published
2021
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28. Multiregional Satellite Precipitation Products Evaluation over Complex Terrain

Author

Derin, Yagmur, Anagnostou, Emmanouil, Berne, Alexis, Borga, Marco, Boudevillain, Brice, Buytaert, Wouter, Chang, Che-Hao, Delrieu, Guy, Hong, Yang, Hsu, Yung Chia, Lavado-Casimiro, Waldo, Manz, Bastian, Moges, Semu, Nikolopoulos, Efthymios I., Sahlu, Dejene, Salerno, Franco, Rodríguez-Sánchez, Juan-Pablo, Vergara, Humberto J., and Yilmaz, Koray K.

Published
2016

37. Floods

Author

Destro, Elisa, primary, Nikolopoulos, Efthymios I., primary, Creutin, Jean-Dominique, primary, and Borga, Marco, primary

Published
2017
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38. Predictive Understanding of Socioeconomic Flood Impact in Data-Scarce Regions Based on Channel Properties and Storm Characteristics: Application in High Mountain Asia (HMA).

Author

Khanam, Mariam, Sofia, Giulia, Rodriguez, Wilmalis, Nikolopoulos, Efthymios I., Binghao Lu, Dongjin Song, and Anagnostou, Emmanouil N.

Subjects
FLOOD risk, EXTREME weather, WEATHER, RAINFALL, FLOODS, DIGITAL elevation models
Abstract

The exposure of High Mountain Asia (HMA) to disaster risks is heightened by extreme weather conditions and the impacts of climate change. Obtaining knowledge about the long-term response of the landscape to hydroclimatic variations in HMA is paramount, as millions of people are affected by these changes every year. During monsoons, substantial human suffering, and damage to crops and infrastructure in populated communities result from the flooding and debris flow caused by the increase in precipitation extremes each year. Although a few initiatives have undertaken the estimation of flood risk locally, the use of traditional techniques in ungauged basins is, unfortunately, not always possible because of the lack of extensive data required. To address this problem, we present in this study a geomorphologically guided machine learning (ML) approach for mapping flood impacts across HMA. We defined socioeconomic flood impact using the Lifeyears Index (LYI), a systematic index that measures the economic cost and loss of life caused by flooding. This index quantifies the importance of the destruction to infrastructure, capital, and housing in an overall assessment. We trained the proposed model with over 6000 flood events, from 1980 to 2020, and their computed five-year and ten-year LYIs. We used as predictors, (1) the five-year rainfall concentrations (which correlate the magnitude of precipitation events with the time of occurrence) of events retrieved from ERA5 daily data; (2) a geomorphic classifier (flood geomorphic potential) based on hydraulic scaling functions automatically derived from an 8 and 30-meter digital elevation model (DEM) for the region and (3) population. This model proved capable of identifying the hotspots of flood susceptibility on a national scale and showing its variability from 1980 to 2022. The study also highlights the severity of the impacts of hydroclimatic extremes in the entire HMA region. The framework is generic and can be used to derive a wide variety of flood vulnerability and subsequent risk maps in data-scarce regions. [ABSTRACT FROM AUTHOR]

Published
2023
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42. An integrated approach to assessing abiotic and biotic threats to post-fire plant species recovery: Lessons from the 2019–2020 Australian fire season

Author

Gallagher, Rachael V., Allen, Stuart P., Mackenzie, Berin D. E., Keith, David A., Nolan, Rachael H., Rumpff, Libby, Gosper, Carl R., Pegg, Geoff S., van Leeuwen, Stephen, Ooi, Mark K. J., Yates, Colin J., Merow, Cory, Williams, Richard J., Nikolopoulos, Efthymios I., Beaumont, Linda J., Auld, Tony D., Gallagher, Rachael V., Allen, Stuart P., Mackenzie, Berin D. E., Keith, David A., Nolan, Rachael H., Rumpff, Libby, Gosper, Carl R., Pegg, Geoff S., van Leeuwen, Stephen, Ooi, Mark K. J., Yates, Colin J., Merow, Cory, Williams, Richard J., Nikolopoulos, Efthymios I., Beaumont, Linda J., and Auld, Tony D.

Abstract

Aim Existing abiotic and biotic threats to plant species (e.g., disease, drought, invasive species) affect their capacity to recover post-fire. We use a new, globally applicable framework to assess the vulnerability of 26,062 Australian plant species to a suite of active threats after the 2019–2020 fires. Location Australia. Time period 2019–2020. Major species studied Plants. Methods Spatial data for existing threats and information on species-level susceptibility were combined with estimates of the extent of range burnt in southern Australia (> 22°S) to assign species against 10 criteria into vulnerability categories (high, medium, low, none, data deficient). We explore in detail results for three threats (drought, disease, feral animals), highlighting where impacts from multiple threats ranked high vulnerability may compound to reduce post-fire recovery. Results Analysis of the full suite of 10 vulnerability criteria, which encompass a broad range of threats, revealed large numbers of species vulnerable to poor post-fire recovery from one or more different hazards (high vulnerability: 1,243 species; medium vulnerability: 2,450 species). Collectively, 457 plant species that burnt extensively (> 50%) across their range are highly vulnerable to poor recovery due to exposure to pre-fire drought conditions (235 species), disease (186 species), or feral animals (97 species). Of these 457 species, 61 are vulnerable to more than one of these three threats, highlighting how a suite of interacting hazards can impact plant recovery after fire. Main conclusions While fire can renew plant populations by stimulating recruitment and resetting competitive interactions, the presence of existing threats in post-fire landscapes jeopardizes recovery. The simultaneous impact of multiple threats that impact recovery can create a suite of hazards that contribute to declines and, potentially, extinction. Our method for rapid post-fire vulnerability assessment can be applied to

Published
2022

47. An integrated approach to assessing abiotic and biotic threats to post‐fire plant species recovery: Lessons from the 2019–2020 Australian fire season

Author

Gallagher, Rachael V., primary, Allen, Stuart P., additional, Mackenzie, Berin D. E., additional, Keith, David A., additional, Nolan, Rachael H., additional, Rumpff, Libby, additional, Gosper, Carl R., additional, Pegg, Geoffrey, additional, van Leeuwen, Stephen, additional, Ooi, Mark K. J., additional, Yates, Colin J., additional, Merow, Cory, additional, Williams, Richard J., additional, Nikolopoulos, Efthymios I., additional, Beaumont, Linda J., additional, Auld, Tony D., additional, and Varner, Morgan, additional

Published
2022
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