Zobrazeno 1 - 10
of 2 736
pro vyhledávání: '"Flood Frequency Analysis"'
Publikováno v:
Discover Geoscience, Vol 2, Iss 1, Pp 1-14 (2024)
Abstract Flood is a widespread climate-related hazard with the potential to occur in almost any geographical location where fluvial processes are active and can occur due to the involvement of multiple factors. Flood frequency analysis (FFA) is consi
Externí odkaz:
https://doaj.org/article/cf6f1a90a8c34c2689d406d4b088ca0d
Publikováno v:
Discover Geoscience, Vol 2, Iss 1, Pp 1-20 (2024)
Abstract Appropriate flood management in a basin requires analysis of peak discharge prediction and flood frequency. The main aim is to find the most suitable distribution model at various gauges for the entire Brahmani-Baitarani River basin for prop
Externí odkaz:
https://doaj.org/article/0a517a3fb9e4459aa8dc7382acd2676f
Publikováno v:
Journal of Nigerian Society of Physical Sciences, Vol 6, Iss 4 (2024)
A suitable probability distribution is required to quantify and estimate hydraulic structure design for risk evaluation and management. The inability of model selection criteria to differentiate, in some cases, among candidate distributions used in t
Externí odkaz:
https://doaj.org/article/256724d9a4204af6a843e58788cd78c0
Autor:
Emrah Yalcin
Publikováno v:
Journal of Water and Climate Change, Vol 15, Iss 5, Pp 2212-2231 (2024)
Climate change is altering flood risk globally, with local variations prompting the necessity for regional assessments to guide the planning and management of water-related infrastructures. This study details an integrated framework for assessing fut
Externí odkaz:
https://doaj.org/article/8e5d5dd27cbe48baaaff7e37a76b7c7f
Publikováno v:
Progress in Earth and Planetary Science, Vol 11, Iss 1, Pp 1-15 (2024)
Abstract Emerging large ensemble climate datasets produced by multiple general circulation models and their downscaling products challenge the limits of hydrodynamic models because of the immense data size. To overcome this new challenge and estimate
Externí odkaz:
https://doaj.org/article/157c39569ddf45669a95ed01c2590dec
Using supervised machine learning for regional hydrological hazard estimation in metropolitan France
Autor:
Qifan Ding, Patrick Arnaud
Publikováno v:
Journal of Hydrology: Regional Studies, Vol 54, Iss , Pp 101872- (2024)
Study region: This study is carried out for 1929 gauged catchments in France, ranging from 1 to 10,000 km², where quality hydrometric observations are available for flood frequency analysis. Study focus: The regional estimation of hydrological hazar
Externí odkaz:
https://doaj.org/article/3f4dc2fe7c1e4c0d8cb583309ee7a1fb
Publikováno v:
Journal of Hydrology: Regional Studies, Vol 53, Iss , Pp 101782- (2024)
Study region: Southeast Australia Study focus: This study examines identification of homogeneous regions for regional flood frequency analysis (RFFA) using 201 gauged catchments and applying principal component analysis (PCA) and cluster analysis. Qu
Externí odkaz:
https://doaj.org/article/81caa16523e44328be7608f5340f6ecc