Efthymios Nikolopoulos

About

Dr. Efthymios Nikolopoulos is an Associate Professor and the Principal Investigator of the Nikolopoulos Research Group. The group is dedicated to advancing the current state-of-the-art in hydrology through scientific discovery and applications. They focus on developing solutions for real-world problems by conducting research in hydrology. Dr. Nikolopoulos leads a team of researchers who share enthusiasm for hydrology research and strive to contribute to the field through innovative approaches and collaborative efforts.

Research topics

• Geography
• Environmental science
• Geology
• Meteorology
• Climatology
• Agroforestry
• Oceanography
• Cartography
• Ecology
• Biology

Selected publications

• Combining global precipitation data and machine learning to predict flood peaks in ungauged areas with similar climate

  Advances in Water Resources · 2024-08-03 · 10 citations

  articleOpen accessSenior authorCorresponding

  Increasing flood risk due to urbanization and climate change poses a significant challenge to societies at global scale. Hydrologic information that is required for understanding flood processes and for developing effective warning procedures is currently lacking in most parts of the world. Procedures that can combine global climate dataset from satellite and reanalysis with fast and low computational cost prediction systems, are attractive solutions for addressing flood predictions in ungauged…

  PublisherDOI

• Global Future Drought Layers Based on Downscaled CMIP6 Models and Multiple Socioeconomic Pathways

  Scientific Data · 2025-02-19 · 9 citations

  articleOpen accessSenior author

  Droughts are a natural hazard of growing concern as they are projected to increase in frequency and severity for many regions of the world. The identification of droughts and their future characteristics is essential to building an understanding of the geography and magnitude of potential drought change trajectories, which in turn is critical information to manage drought resilience across multiple sectors and disciplines. Adding to this effort, we developed a dataset of global historical and pr…

  PublisherOA PDFDOI

• Spatial partitioning of terrestrial precipitation reveals varying dataset agreement across different environments

  Communications Earth & Environment · 2024-04-23 · 5 citations

  articleOpen access

  Abstract The study of the water cycle at planetary scale is crucial for our understanding of large-scale climatic processes. However, very little is known about how terrestrial precipitation is distributed across different environments. In this study, we address this gap by employing a 17-dataset ensemble to provide, for the first time, precipitation estimates over a suite of land cover types, biomes, elevation zones, and precipitation intensity classes. We estimate annual terrestrial precipitat…

  PublisherOA PDFDOI

• Improving fire severity prediction in south-eastern Australia using vegetation-specific information

  Natural hazards and earth system sciences · 2024-09-30 · 5 citations

  articleOpen access

  Abstract. Wildfire is a critical ecological disturbance in terrestrial ecosystems. Australia, in particular, has experienced increasingly large and severe wildfires over the past 2 decades, while globally fire risk is expected to increase significantly due to projected increases in extreme weather and drought conditions. Therefore, understanding and predicting fire severity is critical for evaluating current and future impacts of wildfires on ecosystems. Here, we first introduce a vegetation-typ…

  PublisherOA PDFDOI

• On the Challenges of Simulating Streamflow in Glacierized Catchments of the Himalayas Using Satellite and Reanalysis Forcing Data

  Journal of Hydrometeorology · 2024-03-07 · 4 citations

  articleSenior author

  Abstract Hydrologic assessment of climate change impacts on complex terrains and data-sparse regions like High Mountain Asia is a major challenge. Combining hydrological models with satellite and reanalysis data for evaluating changes in hydrological variables is often the only available approach. However, uncertainties associated with the forcing dataset, coupled with model parameter uncertainties, can have significant impacts on hydrologic simulations. This work aims to understand and quantify…

  PublisherDOI

Recent grants

• Collaborative Research: BoCP-Implementation: BioFI- Biodiversity Forecasting Initiative to Understand Population, Community and Ecosystem Function Under Global Change

  NSF · $300k · 2022–2026

Frequent coauthors

• Emmanouil N. Anagnostou

  University of Connecticut

  99 shared

• Emmanouil N. Anagnostou

  University of Connecticut

  80 shared

• Marco Borga

  University of Padua

  76 shared

• Francesco Marra

  University of Padua

  74 shared

• Viviana Maggioni

  29 shared

• Elisa Destro

  28 shared

• Marika Koukoula

  University of Lausanne

  23 shared

• Zoi Dokou

  21 shared

Labs

• Nikolopoulos Reseach GroupPI

Awards & honors

• NSF award for Collaborative Research: BoCP-Implementation: B…
• NSF IRES project: Post-hurricane recovery of island freshwat…
• FEMA/NJOEM grant for flood prediction and mitigation in New…
• Best goalkeeper in the Sunshine State Conference (2022)
• Female athlete of the year for Florida Tech (2022)

Similar researchers at Rutgers University

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• Weilin Huangh-56
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