Abstract:(1) Background: river ice has a significant impact on nearly 66% of rivers in the Northern Hemisphere. Ice builds up during winter when the flow gradually reduces to its lowest level before the spring melt is initiated. Ice-induced floods can happen quickly, posing a risk to infrastructure, hydropower generation, and public safety, in addition to ecological repercussions from the scouring and erosion of the riverbeds. (2) Methods: we used the annual daily hydrograph to develop a RiTiCE tool that detects the br… Show more
“…Thus, the grid cell representing the river's course at national boundaries corresponds to the waters entering the downstream country. The runoff data sources used for the validation of the applicability of the large-scale hydrology models in the case study transboundary basins are derived from (i) the 1st revision of the RBMPs of the River Basin Districts of Epirus (EL05), Central Macedonia (EL10), Eastern Macedonia (EL11), and Thrace (EL12) (e.g., [45,46]), which contain the official hydrological data of Greece; (ii) the 2nd Second Assessment of Transboundary Rivers, Lakes and Groundwaters [29], which contains interannual averaged river discharge figures in both parts of a transboundary basin; and (iii) the Global Runoff Data Centre (GRDC) [47], which is an international hydrological data and information repository under the auspices of the World Meteorological Organization, with its data being used by numerous scholars [48,49]. All the aforementioned data are publicly available on the internet, with their sources given in the "Data availability statement" section.…”
Section: Large-scale Hydrological Models and Data Sourcesmentioning
Large-scale hydrological modeling is an emerging approach in river hydrology, especially in regions with limited available data. This research focuses on evaluating the performance of two well-known large-scale hydrological models, namely E-HYPE and LISFLOOD, for the five transboundary rivers of Greece. For this purpose, discharge time series at the rivers’ outlets from both models are compared with observed datasets wherever possible. The comparison is conducted using well-established statistical measures, namely, coefficient of determination, Percent Bias, Nash–Sutcliffe Efficiency, Root-Mean-Square Error, and Kling–Gupta Efficiency. Subsequently, the hydrological models’ time series are bias corrected through scaling factor, linear regression, delta change, and quantile mapping methods, respectively. The outputs are then re-evaluated against observations using the same statistical measures. The results demonstrate that neither of the large-scale hydrological models consistently outperformed the other, as one model performed better in some of the basins while the other excelled in the remaining cases. The bias-correction process identifies linear regression and quantile mapping as the most suitable methods for the case study basins. Additionally, the research assesses the influence of upstream waters on the rivers’ water budget. The research highlights the significance of large-scale models in transboundary hydrology, presents a methodological approach for their applicability in any river basin on a global scale, and underscores the usefulness of the outputs in cooperative management of international waters.
“…Thus, the grid cell representing the river's course at national boundaries corresponds to the waters entering the downstream country. The runoff data sources used for the validation of the applicability of the large-scale hydrology models in the case study transboundary basins are derived from (i) the 1st revision of the RBMPs of the River Basin Districts of Epirus (EL05), Central Macedonia (EL10), Eastern Macedonia (EL11), and Thrace (EL12) (e.g., [45,46]), which contain the official hydrological data of Greece; (ii) the 2nd Second Assessment of Transboundary Rivers, Lakes and Groundwaters [29], which contains interannual averaged river discharge figures in both parts of a transboundary basin; and (iii) the Global Runoff Data Centre (GRDC) [47], which is an international hydrological data and information repository under the auspices of the World Meteorological Organization, with its data being used by numerous scholars [48,49]. All the aforementioned data are publicly available on the internet, with their sources given in the "Data availability statement" section.…”
Section: Large-scale Hydrological Models and Data Sourcesmentioning
Large-scale hydrological modeling is an emerging approach in river hydrology, especially in regions with limited available data. This research focuses on evaluating the performance of two well-known large-scale hydrological models, namely E-HYPE and LISFLOOD, for the five transboundary rivers of Greece. For this purpose, discharge time series at the rivers’ outlets from both models are compared with observed datasets wherever possible. The comparison is conducted using well-established statistical measures, namely, coefficient of determination, Percent Bias, Nash–Sutcliffe Efficiency, Root-Mean-Square Error, and Kling–Gupta Efficiency. Subsequently, the hydrological models’ time series are bias corrected through scaling factor, linear regression, delta change, and quantile mapping methods, respectively. The outputs are then re-evaluated against observations using the same statistical measures. The results demonstrate that neither of the large-scale hydrological models consistently outperformed the other, as one model performed better in some of the basins while the other excelled in the remaining cases. The bias-correction process identifies linear regression and quantile mapping as the most suitable methods for the case study basins. Additionally, the research assesses the influence of upstream waters on the rivers’ water budget. The research highlights the significance of large-scale models in transboundary hydrology, presents a methodological approach for their applicability in any river basin on a global scale, and underscores the usefulness of the outputs in cooperative management of international waters.
The Arctic region experiences significant annual hydrologic events, with the spring flood and ice break-up being the most prominent. River ice break-up, in particular, poses high socioeconomic and ecological expenses, including morphological changes and damage to riverine structures. This study aims to investigate the spatiotemporal patterns of river ice in the River Tornionjoki, including the timing of ice break-up at different latitudes. We utilized observation data and remote sensing techniques to track changes in ice patterns overtime on the River Tornionjoki. The study indicates that the ice break-up in the River Tornionjoki basin typically occurs during Apr-Jun based on the reach location in different latitudes; therefore, different stations behave according to their latitudinal location. We observed significant spatial variations in ice break-up timing across the basin, with an earlier break-up in the lower latitudes compared to the upper latitudes. The average ice break-up day in lower latitude stations ranges between 200–205, while in higher latitude stations the average ice break-up day ranges between 215–228.
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