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Technical University of Crete
Technical University of Crete
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| URI | http://purl.tuc.gr/dl/dias/DC333A15-E009-4C3A-BFE6-003E164C6A85 | - |
| Identifier | https://doi.org/10.5194/soild-2-647-2015 | - |
| Identifier | http://www.soil-discuss.net/2/647/2015/soild-2-647-2015.pdf | - |
| Language | en | - |
| Extent | 23 pages | en |
| Title | Development of a statistical tool for the estimation of riverbank erosion probability | en |
| Creator | Varouchakis Emmanouil | en |
| Creator | Βαρουχακης Εμμανουηλ | el |
| Creator | Giannakis Georgios | en |
| Creator | Γιαννακης Γεωργιος | el |
| Creator | Lilli Maria | en |
| Creator | Λιλλη Μαρια | el |
| Creator | Nikolaidis Nikolaos | en |
| Creator | Νικολαιδης Νικολαος | el |
| Creator | Karatzas Giorgos | en |
| Creator | Καρατζας Γιωργος | el |
| Creator | Ioannidou Eleni | en |
| Creator | Ιωαννιδου Ελενη | el |
| Publisher | Copernicus Publications | en |
| Description | Δημοσίευση σε επιστημονικό περιοδικό | el |
| Content Summary | Riverbank erosion affects river morphology and local habitat and results in riparian land loss, property and infrastructure damage, and ultimately flood defence weakening. An important issue concerning riverbank erosion is the identification of the vulnerable ar- 5 eas in order to predict river changes and assist stream management/restoration. An approach to predict vulnerable to erosion areas is to quantify the erosion probability by identifying the underlying relations between riverbank erosion and geomorphological or hydrological variables that prevent or stimulate erosion. In the present work, a combined deterministic and statistical methodology is proposed to predict the probability 10 of presence or absence of erosion in a river section. A physically based model determines the vulnerable to erosion locations by quantifying the potential eroded area. The derived results are used to determine validation locations for the statistical tool performance evaluation. The statistical tool is based on a series of independent local variables and employs the Logistic Regression methodology. It is developed in two 15 forms, Logistic Regression and Locally Weighted Logistic Regression, which both deliver useful and accurate results. The second form though provides the most accurate results as it validates the presence or absence of erosion at all validation locations. The proposed methodology is easy to use, accurate and can be applied to any region and river. | en |
| Type of Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2015-11-06 | - |
| Date of Publication | 2015 | - |
| Subject | Riverbank filtration | en |
| Subject | Riverbank infiltration | en |
| Subject | Water--Riverbank filtration | en |
| Subject | water purification riverbank filtration | en |
| Subject | riverbank filtration | en |
| Subject | riverbank infiltration | en |
| Subject | water riverbank filtration | en |
| Subject | Analysis, Regression | en |
| Subject | Linear regression | en |
| Subject | Regression modeling | en |
| Subject | regression analysis | en |
| Subject | analysis regression | en |
| Subject | linear regression | en |
| Subject | regression modeling | en |
| Bibliographic Citation | E. A. Varouchakis, G. V. Giannakis, M. A. Lilli, E. Ioannidou, N. P. Nikolaidis and G. P. Karatzas, "Development of a statistical tool for the estimation of riverbank erosion probability", SOIL Discuss, vo. 2, pp.647–674, 2015, doi:10.5194/soild-2-647-2015 | en |
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