Περιλαμβάνονται, με χρονολογική σειρά, δημοσιεύσεις στις οποίες έχουν χρησιμοποιηθεί δεδομένα από το εθνικό δίκτυο παρακολούθησης λιμνών.
Δημοσιεύσεις σε επιστημονικά περιοδικά
Papadimos, Dimitris; Papamichail, Dimitris
Performance Evaluation of a Distributed Hydrological Model Using Satellite Data over the Lake Kastoria Catchment, Greece Δημοσίευση σε επιστημονικό περιοδικό
In: Hydrology, vol. 13, iss. 2026, no. 1, 2025, ISSN: 2306-5338.
Περίληψη | Σύνδεσμοι | BibTeX | Ετικέτες: GEOV3, GPM_3IMERGDF, Kastoria lake, MIKE HYDRO River, MIKE SHE, satellite LAI, satellite precipitation, spatially distributed hydrological modeling
@article{hydrology13010002,
title = {Performance Evaluation of a Distributed Hydrological Model Using Satellite Data over the Lake Kastoria Catchment, Greece},
author = {Papadimos, Dimitris and Papamichail, Dimitris},
editor = {Changsen Zhao},
url = {https://www.mdpi.com/2306-5338/13/1/2},
doi = {10.3390/hydrology13010002},
issn = {2306-5338},
year = {2025},
date = {2025-12-20},
urldate = {2025-12-20},
journal = {Hydrology},
volume = {13},
number = {1},
issue = {2026},
abstract = {It might be difficult in many countries to find extended time series of measurements related to parameters of lakes’ hydrology and their interactions with catchments. Nowadays, the combined use of satellite imagery and spatially distributed hydrological models may contribute substantially to this direction. In this study, in order to assess for a long period of years a lake’s surface elevation (LSE) and its water balance components, Lake Kastoria and its catchment, under Greece’s dry-thermal conditions, were selected as the case study. This research employed the MIKE SHE coupled with the MIKE HYDRO River (MHR) hydrological modeling system, fed with precipitation and leaf area index (LAI) data coming from a ground weather station, typical values of LAI for the specific area, and satellite products from NASA for the precipitation and from Copernicus Global Land Service for the LAI. In all cases where satellite data were used, the simulation of the long-term LSE was very satisfactory, with minor to medium changes to the inflow and outflow components of the water balance in both the catchment (from 0.32 to 7.36%) and the lake (from 1.47 to 11.3%). The above changes were also reflected in the runoff coefficients. In conclusion, the above satellite products can adequately be used for the prediction of the LSE. Furthermore, a plethora of quantified information in relation to the catchment’s water balance can be extracted and used in decision-making processes.},
keywords = {GEOV3, GPM_3IMERGDF, Kastoria lake, MIKE HYDRO River, MIKE SHE, satellite LAI, satellite precipitation, spatially distributed hydrological modeling},
pubstate = {published},
tppubtype = {article}
}
It might be difficult in many countries to find extended time series of measurements related to parameters of lakes’ hydrology and their interactions with catchments. Nowadays, the combined use of satellite imagery and spatially distributed hydrological models may contribute substantially to this direction. In this study, in order to assess for a long period of years a lake’s surface elevation (LSE) and its water balance components, Lake Kastoria and its catchment, under Greece’s dry-thermal conditions, were selected as the case study. This research employed the MIKE SHE coupled with the MIKE HYDRO River (MHR) hydrological modeling system, fed with precipitation and leaf area index (LAI) data coming from a ground weather station, typical values of LAI for the specific area, and satellite products from NASA for the precipitation and from Copernicus Global Land Service for the LAI. In all cases where satellite data were used, the simulation of the long-term LSE was very satisfactory, with minor to medium changes to the inflow and outflow components of the water balance in both the catchment (from 0.32 to 7.36%) and the lake (from 1.47 to 11.3%). The above changes were also reflected in the runoff coefficients. In conclusion, the above satellite products can adequately be used for the prediction of the LSE. Furthermore, a plethora of quantified information in relation to the catchment’s water balance can be extracted and used in decision-making processes.