Georgia A Papacharalampous

Cited by

	All	Since 2018
Citations	1756	1720
h-index	19	18
i10-index	22	21

580

290

145

435

201720182019202020212022202329 57 161 348 482 574 93

Public access

View all

5 articles

0 articles

available

not available

Based on funding mandates

Co-authors

Hristos TyralisHellenic Air ForceVerified email at itia.ntua.gr
Demetris KoutsoyiannisProf. Em., Hydrology & Hydrosystems; Dept. Water Resources; School of Civil Engineering; NTU AthensVerified email at itia.ntua.gr
Andreas LangousisAssociate Professor, Department of Civil Engineering, University of Patras (UPatras), GreeceVerified email at upatras.gr
Alberto MontanariProfessor of Hydrology and Water Engineering, University of BolognaVerified email at unibo.it
Elena VolpiUniversità Roma TreVerified email at uniroma3.it
Salvatore GRIMALDIProfessor of Hydrology, Università degli Studi della Tuscia, Viterbo, ItalyVerified email at unitus.it
Simon Michael PapalexiouUniversity of Calgary, CanadaVerified email at ucalgary.ca
Nikos MamassisAssociate Professor of Hydrology; Dept. of Water Resources; School of Civil Engineering; NTU AthensVerified email at itia.ntua.gr
Apostolos BurnetasDepartment of Mathematics, National and Kapodistrian University of AthensVerified email at math.uoa.gr
Sina KhatamiUppsala UniversityVerified email at geo.uu.se
Sarintip TantaneeNaresuan UniversityVerified email at nu.ac.th
Andrea PETROSELLITuscia UniversityVerified email at unitus.it
Sofia NerantzakiVerified email at isc.tuc.gr
rodolfo piscopialibero ricercatoreVerified email at unitus.it
Davide Luciano De LucaUniversità della Calabria - Dipartimento di Ingegneria Informatica, Modellistica, Elettronica eVerified email at unical.it
Yannis MarkonisCzech University of Life Sciences PragueVerified email at fzp.czu.cz
Martin HanelCzech University of Life SciencesVerified email at fzp.czu.cz
Panos N. PapanicolaouProfessor, School of Civil Engineering, National Technical University of AthensVerified email at mail.ntua.gr
Panayiotis DimitriadisDepartment of Water Resources and Environmental Engineering, School of Civil Engineering, NTUAVerified email at itia.ntua.gr
Christos KotsalosEPFLVerified email at epfl.ch

Georgia A Papacharalampous

Researcher at the National Technical University of Athens

Verified email at hydro.ntua.gr

Hydrology Hydroinformatics Water Resources Engineering Forecasting Machine learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Twenty-three Unsolved Problems in Hydrology (UPH)–a community perspective G Blöschl, MFP Bierkens, A Chambel, C Cudennec, G Destouni, A Fiori, ... Hydrological Sciences Journal 64 (10), 1141–1158, 2019	447	2019
A brief review of random forests for water scientists and practitioners and their recent history in water resources H Tyralis, G Papacharalampous, A Langousis Water 11 (5), 910, 2019	280*	2019
Variable Selection in Time Series Forecasting Using Random Forests H Tyralis, G Papacharalampous Algorithms 10 (4), 114, 2017	142	2017
Comparison of stochastic and machine learning methods for multi-step ahead forecasting of hydrological processes GA Papacharalampous, H Tyralis, D Koutsoyiannis Stochastic Environmental Research and Risk Assessment 33 (2), 481–514, 2019	120	2019
Predictability of monthly temperature and precipitation using automatic time series forecasting methods G Papacharalampous, H Tyralis, D Koutsoyiannis Acta Geophysica 66 (4), 807–831, 2018	112	2018
Super ensemble learning for daily streamflow forecasting: Large-scale demonstration and comparison with multiple machine learning algorithms H Tyralis, G Papacharalampous, A Langousis Neural Computing and Applications, 1-16, 2020	71	2020
Evaluation of random forests and Prophet for daily streamflow forecasting GA Papacharalampous, H Tyralis Advances in Geosciences 45, 201–208, 2018	66*	2018
Hydrological post-processing using stacked generalization of quantile regression algorithms: Large-scale application over CONUS H Tyralis, GA Papacharalampous, A Burnetas, A Langousis Journal of Hydrology 577, 123957, 2019	65	2019
Univariate time series forecasting of temperature and precipitation with a focus on machine learning algorithms: A multiple-case study from Greece G Papacharalampous, H Tyralis, D Koutsoyiannis Water Resources Management 32 (15), 5207–5239, 2018	56	2018
Probabilistic hydrological post-processing at scale: Why and how to apply machine-learning quantile regression algorithms G Papacharalampous, H Tyralis, A Langousis, AW Jayawardena, ... Water 11 (10), 2126, 2019	50	2019
How to explain and predict the shape parameter of the generalized extreme value distribution of streamflow extremes using a big dataset H Tyralis, G Papacharalampous, S Tantanee Journal of Hydrology 574, 628–645, 2019	42	2019
One-step ahead forecasting of geophysical processes within a purely statistical framework G Papacharalampous, H Tyralis, D Koutsoyiannis Geoscience Letters 5 (1), 12, 2018	39*	2018
Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: A large-sample experiment at monthly timescale G Papacharalampous, H Tyralis, D Koutsoyiannis, A Montanari Advances in Water Resources 136, 103470, 2020	34	2020
Boosting algorithms in energy research: A systematic review H Tyralis, G Papacharalampous Neural Computing and Applications 33 (21), 14101-14117, 2021	27	2021
Hydrological time series forecasting using simple combinations: Big data testing and investigations on one-year ahead river flow predictability G Papacharalampous, H Tyralis Journal of Hydrology 590, 125205, 2020	27	2020
Global-scale massive feature extraction from monthly hydroclimatic time series: Statistical characterizations, spatial patterns and hydrological similarity G Papacharalampous, H Tyralis, SM Papalexiou, A Langousis, S Khatami, ... Science of The Total Environment 767, 144612, 2021	23	2021
Large-scale assessment of Prophet for multi-step ahead forecasting of monthly streamflow H Tyralis, GA Papacharalampous Advances in Geosciences 45, 147–153, 2018	23	2018
Quantification of predictive uncertainty in hydrological modelling by harnessing the wisdom of the crowd: Methodology development and investigation using toy models G Papacharalampous, D Koutsoyiannis, A Montanari Advances in Water Resources 136, 103471, 2020	22	2020
Forecasting of geophysical processes using stochastic and machine learning algorithms GA Papacharalampous, H Tyralis, D Koutsoyiannis European Water, 161–168, 2017	21	2017
Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale G Papacharalampous, H Tyralis, IG Pechlivanidis, S Grimaldi, E Volpi Geoscience Frontiers 13 (3), 101349, 2022	11	2022

The system can't perform the operation now. Try again later.

Articles 1–20

Citations per year

Duplicate citations

Merged citations

Add co-authorsCo-authors

Follow

Cited by

Co-authors