Automated Author ProfileKalogeropoulos, Kleomenis
Kalogeropoulos, Kleomenis
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 7.6 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Natural hazards are historically a substantial threat to the progress and development of human communities. Floods hold a dominant position among these specific phenomena due to their fre-quent occurrence as well as their large spatial spread. Certainly, the aforementioned facts become more visible under the light of the assessment of the dramatic effects brought about by their occur-rence. Consequently, the need to deal with the impact of floods on human communities with an effective way leads to a systematic involvement of the international scientific community on the subject of "Management of Natural Hazards".The present study describes an attempt to model surface runoff in a typical ungauged basin, which is directly related to catastrophic flood events, by creating a system based on GIS technology. The main object was to construct a direct unit hydrograph for an excess rainfall by estimating the stream flow response at the outlet of a watershed. Specifically, the methodology was based on the creation of a spatial database in GIS environment and on data editing. Moreover, rainfall time-series data came from Hellenic National Meteorological Service and they were processed in order to calculate flow time and the runoff volume. Apart from the meteorological data, background data such as topography, drainage network, land cover and geological data were also collected. A high resolution DEM was of great importance in order to achieve the final result. The study area is the sub-basin of Archaia Olympia (Kladeos sub-basin) in Greece, and the examined event occurred on February 5th, 2012.
Authors
- Gioti, Evangelia ;
- Riga, Chrisoula ;
- Kalogeropoulos, Kleomenis ;
- Chalkias, Christos