Department of Civil, Construction and Environmental Engineering, Center of Complex Hydrosystems Research, The University of Alabama, 35487 Tuscaloosa, USA
Department of Civil, Construction and Environmental Engineering, Center of Complex Hydrosystems Research, The University of Alabama, 35487 Tuscaloosa, USA
Department of Civil, Construction and Environmental Engineering, Center of Complex Hydrosystems Research, The University of Alabama, 35487 Tuscaloosa, USA
Department of Civil, Construction and Environmental Engineering, Center of Complex Hydrosystems Research, The University of Alabama, 35487 Tuscaloosa, USA
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2,835
751
106
3,692
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Cumulative views and downloads
(calculated since 21 Feb 2024)
Total article views: 2,568 (including HTML, PDF, and XML)
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EndNote
2,096
411
61
2,568
98
77
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HTML: 2,096
PDF: 411
XML: 61
Total: 2,568
Supplement: 98
BibTeX: 77
EndNote: 102
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Total article views: 1,124 (including HTML, PDF, and XML)
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739
340
45
1,124
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41
HTML: 739
PDF: 340
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Total: 1,124
BibTeX: 42
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Cumulative views and downloads
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Total article views: 3,692 (including HTML, PDF, and XML)
Thereof 3,584 with geography defined
and 108 with unknown origin.
Total article views: 2,568 (including HTML, PDF, and XML)
Thereof 2,494 with geography defined
and 74 with unknown origin.
Total article views: 1,124 (including HTML, PDF, and XML)
Thereof 1,090 with geography defined
and 34 with unknown origin.
This study utilizes the global copula Bayesian model averaging technique for accurate and reliable flood modeling, especially in coastal regions. By integrating multiple precipitation datasets within this framework, we can effectively address sources of error in each dataset, leading to the generation of probabilistic flood maps. The creation of these probabilistic maps is essential for disaster preparedness and mitigation in densely populated areas susceptible to extreme weather events.
This study utilizes the global copula Bayesian model averaging technique for accurate and...
