1. Αποθετήριο Παραδοτέων Υποτρόφων Δράσεων ΕΣΠΑ Τριτοβάθμιας Εκπαίδευσης 2017-2023
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3. Ερευνητικές ομάδες

Τύπος:	Άρθρο σε επιστημονικό περιοδικό
Τίτλος:	Spatio-temporal interpolation and bias correction ordering analysis for hydrological simulations: an assessment on a mountainous river basin
Εναλλακτικός τίτλος:	Ανάλυση κατάταξης χωροχρονικής παρεμβολής και διόρθωσης μεροληψίας για υδρολογικές προσομοιώσεις: Αξιολόγηση σε ορεινή λεκάνη απορροής ποταμού
Συγγραφέας:	[EL] Σκουληκάρης, Χαράλαμπος[EN] Skoulikaris, Charalampos [EL] Βενετσάνου, Παναγιώτα[EN] Venetsanou, Panagiota [EL] Λάζογλου, Γεωργία[EN] Lazoglou, Georgia [EL] Αναγνωστοπούλου, Χριστίνα[EN] Anagnostopoulou, Christina [EL] Βουδούρης, Κωνσταντίνος[EN] Voudouris, Konstantinos
Ημερομηνία:	20/02/2022
Περίληψη:	Triggering hydrological simulations with climate change gridded datasets is one of the prevailing approaches in climate change impact assessment at a river basin scale, with bias correction and spatio-temporal interpolation being functions routinely used on the datasets preprocessing. The research object is to investigate the dilemma arisen when climate datasets are used, and shed light on which process—i.e., bias correction or spatio-temporal interpolation—should go first in order to achieve the maximum hydrological simulation accuracy. In doing so, the fifth generation of the European Centre for Medium Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) temperature and precipitation products of 9 × 9 km spatial resolution, which are considered as the reference data, are initially compared with the same hindcast variables of a regional climate model of 12.5 × 12.5 km spatial resolution over a specific case study basin and for a 10-year period (1991–2000). Thereafter, the climate model’s variables are (a) bias corrected followed by their spatial interpolation at the reference resolution of 9 × 9 km with the use of empirical quantile mapping and spatio-temporal kriging methods respectively, and (b) spatially downscaled and then bias corrected by using the same methods as before. The derived outputs from each of the produced dataset are not only statistically analyzed at a climate variables level, but they are also used as forcings for the hydrological simulation of the river runoff. The simulated runoffs are compared through statistical performance measures, and it is established that the discharges attributed to the bias corrected climate data followed by the spatio-temporal interpolation present a high degree of correlation with the reference ones. The research is considered a useful roadmap for the preparation of gridded climate change data before being used in hydrological modeling.
Γλώσσα:	Αγγλικά
Σελίδες:	18
DOI:	10.3390/w14040660
EISSN:	2073-4441
Θεματική κατηγορία:	[EL] Άλλες φυσικές επιστήμες[EN] Other natural sciences
Λέξεις-κλειδιά:	spatio-temporal kriging; bias correction; climate change; gridded dataset; hydrologic modelling; Greece
Κάτοχος πνευματικών δικαιωμάτων:	© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Όροι και προϋποθέσεις δικαιωμάτων:	This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
Ηλεκτρονική διεύθυνση του τεκμηρίου στον εκδότη:	https://www.mdpi.com/2073-4441/14/4/660
Ηλεκτρονική διεύθυνση περιοδικού:	https://www.mdpi.com/journal/water
Τίτλος πηγής δημοσίευσης:	Water
Τεύχος:	4
Τόμος:	14
Σελίδες τεκμηρίου (στην πηγή):	Article no 660
Σημειώσεις:	The research is co-financed by Greece and European Union (European Social Fund- ESF) through the Operational Program “Human Resources Development, Education and Lifelong Learning 2014–2020” in the context of the project “Optimization of hydrological simulation at basin scale under climate conditions with the use of spatial and spatio-temporal methods” (MIS 5052159).
Εμφανίζεται στις συλλογές:	Ερευνητικές ομάδες