EconPapers    
Economics at your fingertips  
 

Probabilistic dam breach flood modeling: the case of Valsamiotis dam in Crete

Sofia Sarchani and Aristeidis G. Koutroulis ()
Additional contact information
Sofia Sarchani: Technical University of Crete
Aristeidis G. Koutroulis: Technical University of Crete

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2022, vol. 114, issue 2, No 28, 1763-1814

Abstract: Abstract Flooding from dam failure has disastrous downstream impacts resulting in loss of life, damage to buildings and infrastructure, and crop destruction. This study aims to evaluate the potential flood risks due to the hypothetical overtopping breach of the Valsamiotis dam and assess potential impacts on the downstream residential and rural areas. The analysis is based on seven peak discharge exceedance probability (EP) scenarios through a Monte Carlo approach derived by the McBreach software for a plausible range of breach parameters. The flood wave progression was simulated with the use of HEC-RAS 2D and a high-resolution digital elevation model. The overall inundated area ranged from 7.59 to 7.79 km2. Uncertainty of floodplain roughness was examined by considering a range of Manning’s roughness coefficient. Maximum flood depths and velocities were examined, and flood arrival times at various depths were analyzed to support flood risk mapping. The monetary losses of the affected buildings were estimated to vary from 20 to 37 million euros. The annual losses of crop yield were also considerable, ranging between 8.5 and 8.8 million euros. The breach formation time as well as the final bottom width of the breach are found the most critical parameters affecting the peak breach discharge. The results show that the nearby downstream villages are at high risk for all the scenarios. In particular, at Vatolakkos village the maximum depth values ranged from 4.8 to 8.6 m, which was achieved in 7–17 min after the dam breaking, whereas at Koufos village reached on average 2.1 m in 27–38 min, according to the EP scenarios. Moving downstream at the catchment outlet, Platanias coastal area is influenced to a lesser degree. An extensive area of fruit trees including oranges and avocados, of the order of 6.62–6.78 km2, is simulated as highly impacted. The range of probabilistic dam breaching and associated downstream inundation simulations is a comprehensive framework to quantify the uncertainty of flood risks due to dam breach. The results can facilitate decision-making toward management planning for civil protection, emergency action plans, and well-organized adaptation to risks related to life and property caused by possible dam failure.

Keywords: Dam breach; Exceedance probability; Monte Carlo; Uncertainty; Monetary losses; Flood risk (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s11069-022-05446-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:114:y:2022:i:2:d:10.1007_s11069-022-05446-0

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-022-05446-0

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:nathaz:v:114:y:2022:i:2:d:10.1007_s11069-022-05446-0