Stelian Curceac

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Paul HarrisRothamsted ResearchVerified email at rothamsted.ac.uk
Peter M AtkinsonDistinguished Professor and Executive Dean, Faculty of Science and Technology, Lancaster UniversityVerified email at lancaster.ac.uk
Lianhai WuRothamsted ResearchVerified email at rothamsted.ac.uk
Taha BMJ OuardaInstitut national de la recherche scientifique (INRS-ETE)Verified email at ete.inrs.ca
Camille TernynckPhD applied mathematics - ingénieure de rechercheVerified email at univ-lille.fr
Fateh ChebanaProfessor, Université du Québec, INRSVerified email at inrs.ca
Sophie Dabo-Niangprofesseur de mathématiques appliquées, université de LilleVerified email at univ-lille.fr
Demetris KoutsoyiannisProf. Em., Hydrology & Hydrosystems; Dept. Water Resources; School of Civil Engineering; NTU AthensVerified email at itia.ntua.gr
Simon Michael PapalexiouAssociate Professor, University of Calgary, CanadaVerified email at ucalgary.ca
Vasileia VasilakiBrunel University LondonVerified email at brunel.ac.uk
Evangeline Mae CorcoranThe Alan Turing InstituteVerified email at turing.ac.uk
Mehdi H. AfsharTechnical University of HamburgVerified email at tuhh.de
Muhammad Mohsin RazaData Science and Environment, Department of Mathematics, University of ExeterVerified email at exeter.ac.uk
Azam LashkariPostDoctoral ScientistVerified email at jic.ac.uk
Nikolaos EfthimiouCzech University of Life SciencesVerified email at fzp.czu.cz

Stelian Curceac

KIT/IMK-IFU

Verified email at kit.edu - Homepage

data analysis statistics forecasting environmental modelling hydrology


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Short-term air temperature forecasting using Nonparametric Functional Data Analysis and SARMA models S Curceac, C Ternynck, TBMJ Ouarda, F Chebana, SD Niang Environmental Modelling & Software 111, 394-408, 2019	52	2019
An evaluation of automated GPD threshold selection methods for hydrological extremes across different scales S Curceac, PM Atkinson, A Milne, L Wu, P Harris Journal of Hydrology 585, 124845, 2020	17	2020
Adjusting for conditional bias in process model simulations of hydrological extremes: An experiment using the North Wyke Farm Platform S Curceac, PM Atkinson, A Milne, L Wu, P Harris Frontiers in Artificial Intelligence 3, 565859, 2020	10	2020
Elucidating the performance of hybrid models for predicting extreme water flow events through variography and wavelet analyses S Curceac, A Milne, PM Atkinson, L Wu, P Harris Journal of Hydrology 598, 126442, 2021	6	2021
A case study on the effects of data temporal resolution on the simulation of water flux extremes using a process-based model at the grassland field scale L Wu, S Curceac, PM Atkinson, A Milne, P Harris Agricultural Water Management 255, 107049, 2021	3	2021
Current data and modeling bottlenecks for predicting crop yields in the United Kingdom E Corcoran, M Afshar, S Curceac, A Lashkari, MM Raza, S Ahnert, ... Frontiers in Sustainable Food Systems 7, 1023169, 2023	1	2023
Investigation of probabilistic, deterministic and hybrid models for improved characterisation of hydrological extremes across varying temporal scales S Curceac PQDT-Global, 2022		2022
Short-term forecasting of meteorological time series using Nonparametric Functional Data Analysis (NPFDA) S Curceac, C Ternynck, T Ouarda AGU Fall Meeting Abstracts 2015, A33M-0401, 2015		2015
Clustering of extreme events in typical stochastic models A Mystegniotis, VK Vasilaki, I Pappa, S Curceac, D Saltouridou, ... EGU General Assembly Conference Abstracts, EGU2013-4599, 2013		2013
Advanced Quality Control Report 1 S Curceac, J Hawkins, P Harris
Geophysical time series vs. financial time series of agricultural products: similarities and differences VK Vasilaki, S Curceac, SM Papalexiou, D Koutsoyiannis

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