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https://hdl.handle.net/123456789/1691| Τύπος: | Άρθρο σε επιστημονικό περιοδικό |
| Τίτλος: | Remote sensing methodology for roughness estimation in ungauged streams for different hydraulich/hydrodynamic modeling approaches |
| Συγγραφέας: | [EL] Παπαϊωάννου, Γεώργιος[EN] Papaioannou, Georgios [EL] Μαρκογιάννη, Βασιλική[EN] Markogianni, Vassiliki [EL] Λουκάς, Αθανάσιος[EN] Loukas, Athanasios [EL] Δημητρίου, Ηλίας[EN] Dimitriou, Elias |
| Ημερομηνία: | 29/03/2022 |
| Περίληψη: | This study investigates the generation of spatially distributed roughness coefficient maps based on image analysis and the extent to which those roughness coefficient values affect the flood inundation modeling using different hydraulic/hydrodynamic modeling approaches ungauged streams. Unmanned Aerial Vehicle (UAV) images were used for the generation of high-resolution Orthophoto mosaic (1.34 cm/px) and Digital Elevation Model (DEM). Among various pixel-based and object-based image analyses (OBIA), a Grey-Level Co-occurrence Matrix (GLCM) was eventually selected to examine several texture parameters. The combination of local entropy values (OBIA method) with Maximum Likelihood Classifier (MLC; pixel-based analysis) was highlighted as a satisfactory approach (65% accuracy) to determine dominant grain classes along a stream with inhomogeneous bed composition. Spatially distributed roughness coefficient maps were generated based on the riverbed image analysis (grain size classification), the size-frequency distributions of river bed materials derived from field works (grid sampling), detailed land use data, and the usage of several empirical formulas that used for the estimation of Manning’s n values. One-dimensional (1D), two-dimensional (2D), and coupled (1D/2D) hydraulic modeling approaches were used for flood inundation modeling using specific Manning’s n roughness coefficient map scenarios. The validation of the simulated flooded area was accomplished using historical flood extent data, the Critical Success Index (CSI), and CSI penalization. The methodology was applied and demonstrated at the ungauged Xerias stream reach, Greece, and indicated that it might be applied to other Mediterranean streams with similar characteristics and flow conditions. |
| Γλώσσα: | Αγγλικά |
| Σελίδες: | 22 |
| DOI: | 10.3390/w14071076 |
| EISSN: | 2073-4441 |
| Θεματική κατηγορία: | [EL] Άλλες φυσικές επιστήμες[EN] Other natural sciences |
| Λέξεις-κλειδιά: | HEC-RAS; flood inundation modeling; modeling approach; spatial distributed roughness coefficient; UAV; remote sensing; image processing; image texture; river bed material mapping |
| 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/). |
| Διατίθεται ανοιχτά στην τοποθεσία: | https://www.researchgate.net/publication/359578352_Remote_Sensing_Methodology_for_Roughness_Estimation_in_Ungauged_Streams_for_Different_HydraulicHydrodynamic_Modeling_Approaches |
| Ηλεκτρονική διεύθυνση του τεκμηρίου στον εκδότη: | https://www.mdpi.com/2073-4441/14/7/1076 |
| Ηλεκτρονική διεύθυνση περιοδικού: | https://www.mdpi.com/journal/water |
| Τίτλος πηγής δημοσίευσης: | Water |
| Τεύχος: | 7 |
| Τόμος: | 14 |
| Σελίδες τεκμηρίου (στην πηγή): | Article no 1076 |
| Σημειώσεις: | This research is co-financed by Greece and the European Union (European Social FundESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning 2014–2020» in the context of the project “Remote sensing methodology for roughness estimation in ungauged streams and sensitivity analysis of floods using different hydraulic/hydrodynamic modeling approaches (1D,2D,1D/2D)” (MIS 5048553). |
| Εμφανίζεται στις συλλογές: | Ερευνητικές ομάδες |
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